Events Archive
PhD Seminar: Mixed Graphical Model for Surveys Under Informative Design, Hao Sun
Presenter: Hao Sun, PhD Candidate in Statistics
Title: Mixed Graphical Model for Surveys Under Informative Design Read more about PhD Seminar: Mixed Graphical Model for Surveys Under Informative Design, Hao Sun
AAPI Heritage Month Celebration
To celebrate Asian American and Pacific Islander (AAPI) Heritage Month in May, the Ames AAPI community and other participating organizations (listed below) will hold a celebration event at 4:30 pm on May 7th in the Sunroom of ISU’s Memorial Union. The event will include opening remarks by Ames City Mayor John Haila and ISU Associate Provost for Faculty Dr. Read more about AAPI Heritage Month Celebration
Sarah Nusser Retirement Party
Monday, May 2nd the Department of Statistics will gather to celebrate the retirement of Sarah Nusser. Join us in the Speer Room of Reiman Gardens from 3:30-5:30pm where you can enjoy small bites, cake, and refreshments. Read more about Sarah Nusser Retirement Party
Departmental Spring Breakfast at Inis Grove Park - It's On!
If you haven’t done so already, please complete the short survey to help us estimate how much food to bring. https://iastate.qualtrics.com/jfe/form/SV_cUZTNstpGtIxRhs Read more about Departmental Spring Breakfast at Inis Grove Park - It's On!
Seminar: Ping-Shou Zhong, University of Illinois Chicago
Presenter: Dr. Ping-Shou Zhong, University of Illinois Chicago
Time: 11:00 AM Central Time, Monday, April 25, 2022
Title: Change-point detection and identification for high-dimensional functional data Read more about Seminar: Ping-Shou Zhong, University of Illinois Chicago
WiDS Ames
Date: April 21, 2022
Time: 2:00 pm - 5:00 pm CST
Location: Zoom (Register to receive link)
Anna Peterson & Laura Ziegler, "Building a Multiple Linear Regression Model With LEGO Brick Data"
Title: Building a Multiple Linear Regression Model With LEGO Brick Data
Presented By: Anna Peterson and Laura Ziegler, Iowa State University Read more about Anna Peterson & Laura Ziegler, "Building a Multiple Linear Regression Model With LEGO Brick Data"
Wen Zhou, Colorado State: Integrative Group Factor Model for Variable Clustering on Temporally Dependent Date: Optimality and Algorithm
Presenter: Dr. Wen Zhou, Colorado State University
Time: 11:00 AM Central Time, Monday, April 18, 2022
Title: Integrative Group Factor Model for Variable Clustering on Temporally Dependent Date: Optimality and Algorithm Read more about Wen Zhou, Colorado State: Integrative Group Factor Model for Variable Clustering on Temporally Dependent Date: Optimality and Algorithm
PhD Seminar: Miranda Tilberg, "Confidence intervals for the utilization distribution overlap index (UDOI)"
Location: Snedecor 1109 (live stream available at https://iastate.zoom.us/j/91269172339?pwd=M2xMSUJxZkxxWm9FcEdhbTNhODJOdz09)
Presenter: Miranda Tilberg, PhD Candidate in Statistics
Title: Confidence intervals for the utilization distribution overlap index (UDOI) Read more about PhD Seminar: Miranda Tilberg, "Confidence intervals for the utilization distribution overlap index (UDOI)"
Leah R. Johnson, Virginia Tech: "Strategic vs Tactical Modeling Approaches to Predicting Mosquito-borne Disease in the Americas"
Presenter: Dr. Leah R. Johnson, Virginia Tech University
Time: 11:00 AM Central Time, Monday, April 11, 2022
Title: Strategic vs Tactical Modeling Approaches to Predicting Mosquito-borne Disease in the Americas Read more about Leah R. Johnson, Virginia Tech: "Strategic vs Tactical Modeling Approaches to Predicting Mosquito-borne Disease in the Americas"
PhD Seminar: Audrey McCombs
Date: Wednesday, April 6, 2022
Time: 8:15 AM CDT
Zoom link: Please click this URL to start or join. https://iastate.zoom.us/j/91558404255?pwd=TkhhbUNJN1hUSEJpTjAzbEtQbU5pUT09
Or, go to https://iastate.zoom.us/join and enter meeting ID: 915 5840 4255 and password: 010136 Read more about PhD Seminar: Audrey McCombs
Alexander Strang, University of Chicago: From local to global structure in random edge flows
Presenter: Dr. Alexander Strang, University of Chicago
Time: 11:00 AM Central Time, Monday, April 4, 2022
Title: From Local to Global Structure in Random Edge Flows Read more about Alexander Strang, University of Chicago: From local to global structure in random edge flows
Xiangqin Cui, Emory University: VA Electronic Medical Records for Research – Challenges and Opportunities
Presenter: Dr. Xiangqin Cui, Emory University
Time: 11:00 AM Central Time, Monday, March 28, 2022
Title: VA Electronic Medical Records for Research – Challenges and Opportunities Read more about Xiangqin Cui, Emory University: VA Electronic Medical Records for Research – Challenges and Opportunities
Lingzhou Xue, Penn State University: An Additive Graphical Model for Discrete Data
Abstract: We introduce a nonparametric graphical model for discrete node variables based on additive conditional independence. Additive conditional independence is a three-way statistical relation that shares similar properties with conditional independence by satisfying the semi-graphoid axioms. Based on this relation we build an additive graphical model for discrete variables that does not suffer from the restriction of a parametric model such as the Ising model. Read more about Lingzhou Xue, Penn State University: An Additive Graphical Model for Discrete Data
Stat-ers academic and professional development event
Stat-ers academic and professional development event:
Visit from Samuel Benidt ISU Alum
Senior Decision Science Consultant at Walt Disney
Read more about Stat-ers academic and professional development event
Yuhlong Lio, University of South Dakota: Robust Control Charts for Percentiles Based on Location-Scale Family of Distributions
Abstract: Robust control charts for percentiles based on location-scale family of distributions are proposed. In the construction of control charts for percentiles, when the underlying distribution of the quality measurement is unknown, we study the problem of discriminating different possible candidate distributions in the location-scale family of distributions and obtain control charts for percentiles which are insensitive to model mis-specification. Read more about Yuhlong Lio, University of South Dakota: Robust Control Charts for Percentiles Based on Location-Scale Family of Distributions
Won Chang, University of Cincinnati: Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments
Abstract: Most organisms exhibit various endogenous oscillating behaviors which provide crucial information as to how the internal biochemical processes are connected and regulated. Understanding the molecular mechanisms behind these oscillators requires interdisciplinary efforts combining both biological and computer experiments, as the latter can complement the former by simulating perturbed conditions with higher resolution. Read more about Won Chang, University of Cincinnati: Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments
Arni Rao, Augusta University: Topology and analysis of SARS-CoV-2
Presenter: Dr. Arni Rao, Medical College of Georgia and Department of Mathematics, Augusta University
Time: 11:00 AM Central Time, Monday, Feb 21, 2022
Title: Topology and analysis of SARS-CoV-2 Read more about Arni Rao, Augusta University: Topology and analysis of SARS-CoV-2
Seminar: Tracy Ke, Harvard
Abstract: The probabilistic topic model imposes a low-rank structure on the expectation of the corpus matrix. Therefore, singular value decomposition (SVD) is a natural tool of dimension reduction. We propose an SVD-based method for estimating a topic model. Our method constructs an estimate of the topic matrix from only a few leading singular vectors of the corpus matrix, and has a great advantage in memory use and computational cost for large-scale corpora. Read more about Seminar: Tracy Ke, Harvard
Seminar: Peng Ding, U.C. Berkeley
Title: To adjust or not to adjust? Estimating the average treatment effect in randomized experiments with missing covariates Read more about Seminar: Peng Ding, U.C. Berkeley
Seminar: Dae Gyu Jang, Iowa State University
Title: Optimal Split Questionnaire Designs based on Multivariate Ordinal Data Read more about Seminar: Dae Gyu Jang, Iowa State University
PhD Seminar: Variable screening in ultra-high dimensional linear regressions
Presenter: Run Wang, PhD candidate in Statistics Read more about PhD Seminar: Variable screening in ultra-high dimensional linear regressions
Ph.D. Seminar: Gang Han, "Received signal strength based animal localization and movement modeling"
Presenter: Gang Han, Ph.D Candidate in Statistics
Title: Received signal strength (RSS) based animal localization and movement modeling Read more about Ph.D. Seminar: Gang Han, "Received signal strength based animal localization and movement modeling"
Adam Runions, University of Calgary: Modeling Leaf Shape Development & Diversity
Adam Runions, University of Calgary
Modeling Leaf Shape Development & Diversity Read more about Adam Runions, University of Calgary: Modeling Leaf Shape Development & Diversity
Seminar: Stephan Huckemann, University of Gottingen
Presenter: Stephan Huckemann, University of Goettingen Read more about Seminar: Stephan Huckemann, University of Gottingen
Seminar: Naveen Naidu Narisetty, University of Illinois at Urbana-Champaign
Presenter: Naveen Narisetty, University of Illinois at Urbana-Champaign
Title: Censored Quantile Regression with a Cure Proportion using Data Augmentation Read more about Seminar: Naveen Naidu Narisetty, University of Illinois at Urbana-Champaign
Ph.D. Seminar, Geoffrey Thompson: CatSIM, A Similarity Metric for Categorical Images
Presenter: Geoffrey Z. Thompson, Ph.D. Candidate in Statistics
Title: CatSIM: A Similarity Metric for Categorical Images Read more about Ph.D. Seminar, Geoffrey Thompson: CatSIM, A Similarity Metric for Categorical Images
Daniela Witten, University of Washington: Selective inference for trees
Abstract: As datasets grow in size, the focus of data collection has increasingly shifted away from testing pre-specified hypotheses, and towards hypothesis generation. Researchers are often interested in performing an exploratory data analysis to generate hypotheses, and then testing those hypotheses on the same data. Unfortunately, this type of 'double dipping' can lead to highly-inflated Type 1 errors. In this talk, I will consider double-dipping on trees. Read more about Daniela Witten, University of Washington: Selective inference for trees
Adrian Lam, Ohio State University: Competition dynamics of phytoplankton species in eutrophic water columns
Title: Competition dynamics of phytoplankton species in eutrophic water columns Read more about Adrian Lam, Ohio State University: Competition dynamics of phytoplankton species in eutrophic water columns
Jae-Kwang Kim, Iowa State University, Weight model approach to Bayesian inference under informative sampling
Abstract: In probability sampling, the first-order inclusion probabilities are available for each unit in the sample. If the first-order inclusion probability is correlated with the study variable at hand, even after adjusting for the covariates in the model, then the sampling design becomes informative and the naive analysis ignoring the sampling design can lead to biased estimation. How to handle informative sampling for analytic inference with survey data is an important practical problem. Read more about Jae-Kwang Kim, Iowa State University, Weight model approach to Bayesian inference under informative sampling
STATers Tailgate
On October 23rd for the football game vs. Oklahoma State, STATers will be hosting a tailgate party in the parking lot of Jack Trice Stadium. There will be two spaces reserved where they will be grilling hotdogs/hamburgers and watching football! The tailgating event starts at 11:30 and the game starts at 2:30pm. Read more about STATers Tailgate
Derrick Rollins, Iowa State University: Dynamic Regression – Proposing a New Modeling Framework in Regression When Response Behavior is Not Static but Dynamic
Presenter: Derrick Rollins, Iowa State University
Title: Dynamic Regression – Proposing a New Modeling Framework in Regression When Response Behavior is Not Static but Dynamic Read more about Derrick Rollins, Iowa State University: Dynamic Regression – Proposing a New Modeling Framework in Regression When Response Behavior is Not Static but Dynamic
Zhijun Wu, Iowa State University: Social Distancing Is a Social Dilemma Game Played by Every Individual against his/her Population
Speaker: Zhijun Wu, Iowa State
Title: Social Distancing Is a Social Dilemma Game Played by Every Individual against his/her Population Read more about Zhijun Wu, Iowa State University: Social Distancing Is a Social Dilemma Game Played by Every Individual against his/her Population
Seminar: Annie Qu, Correlation Tensor Decomposition and Its Application in Spatial Imaging Data
Title: Correlation Tensor Decomposition and Its Application in Spatial Imaging Data Read more about Seminar: Annie Qu, Correlation Tensor Decomposition and Its Application in Spatial Imaging Data
Seminar: Adaptive variational Bayes: Optimality, computation and applications
Speaker: Lizhen Lin, University of Notre Dame Read more about Seminar: Adaptive variational Bayes: Optimality, computation and applications
Seminar: Stochastic processes with semi-long range dependence
Speaker: Farzad Sabzikar, Iowa State University Read more about Seminar: Stochastic processes with semi-long range dependence
Stat-ers academic and professional development event
Visit from Carol Bogacz ISU Alum, Data Scientist at Burns & McDonnell
Read more about Stat-ers academic and professional development event
Residual Refitting Inference for High-Dimensional Linear Model
Presenter: Yumou Qiu, Iowa State University Read more about Residual Refitting Inference for High-Dimensional Linear Model
Seminar: Functional Data in Constrained Spaces
Presenter: John Aston, Cambridge University Read more about Seminar: Functional Data in Constrained Spaces
Vijay Nair: When did regression become so complicated? Machine Learning: Algorithms, Interpretability, and Applications in Banking
Presenter: Vijay Nair, Wells Fargo and University of Michigan, Ann Arbor Read more about Vijay Nair: When did regression become so complicated? Machine Learning: Algorithms, Interpretability, and Applications in Banking
Fall 2021 Welcome Seminar
You are invited to the Fall 2021 Welcome Seminar for the Department of Statistics. The seminar will be presented from 11:00-11:50 A.M. on Monday, August 23. The event will highlight some departmental accomplishments from the past year, discuss future events, present student awards, and introduce new students, faculty, and staff.
You can join via Zoom or if you prefer to attend the seminar in person may join in 0198 Parks Library, where face masks are encouraged. Read more about Fall 2021 Welcome Seminar
Seminar: Resolving Real Biological Sequences with Accurate Abundance Estimation from Noisy Illumina Amplicon Data
Abstract: Amplicon sequencing has been widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and accurately quantifying their abundance from noisy amplicon sequence data is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, along with errors generated during Polymerase Chain Reaction (PCR) and sequencing. Read more about Seminar: Resolving Real Biological Sequences with Accurate Abundance Estimation from Noisy Illumina Amplicon Data
Seminar: Functional ANOVA-type methods with interpretable visualization for comparisons among groups of time series
Abstract: Data sampled densely in space and time have become increasingly abundant as a result of advances in modern technology. However, the presence of complex dependence and current computational limitations have made many classical inferential approaches practically infeasible. Read more about Seminar: Functional ANOVA-type methods with interpretable visualization for comparisons among groups of time series
Seminar: Exploratory Analysis of High-Dimensional Data with Visual Tools
Abstract: Exploratory data analysis and dimension reduction techniques serve as the backbone for developing visual tools designed to foster new ideas and an understanding of the underlying phenomenon of interest. The tour is a dynamic visualization technique for exploratory data analyses of high-dimensional numeric data consisting of a smooth sequence of d-dimensional projections from p-dimensional Euclidean space. Read more about Seminar: Exploratory Analysis of High-Dimensional Data with Visual Tools
Principal Component Analysis of Discrete Datasets
Abstract: We propose a Gaussian copula based method to perform principal component analysis for discrete data. By assuming the data are from a discrete distributions in the Gaussian copula family, we can consider the discrete random vectors are generated from a latent multivariate normal random vector. So we first obtain an estimate of the correlation matrix of latent multivariate normal distribution, then we use the estimated latent correlation matrix to get the estimates of principal components. Read more about Principal Component Analysis of Discrete Datasets
Seminar: Statistical Inference for Mean Functions of 3D Functional Objects
Abstract: Functional data analysis has become a powerful tool for conducting statistical analysis for complex objects, such as curves, images, shapes, and manifold-valued data. Among these data objects, 2D or 3D images obtained using medical imaging technologies have been attracting researchers' attention. Examples are functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), which provide a very detailed characterization of brain activity. Read more about Seminar: Statistical Inference for Mean Functions of 3D Functional Objects
Seminar: A RKHS Approach for Variable Selection in High Dimensional Functional Linear Models
Abstract: There has been a recent surge in applications of high-dimensional functional data analysis. We explore functional linear regression by focusing on the large-scale scenario that scalar response is associated with potentially an ultra-large number of functional predictors in the setting of the reproducing kernel Hilbert space (RKHS) framework. Read more about Seminar: A RKHS Approach for Variable Selection in High Dimensional Functional Linear Models
Seminar: Estimation and Inference of Quantile Spatially Varying Coefficient Models over Complicated Domains
Abstract: Regression analysis is frequently used in the analyses of spatial data. In this paper, we propose a flexible quantile spatially varying coefficient model to assess how conditional quantiles of the response depend on covariates, allowing the coefficient function to vary with the spatial locations. The model can be used to explore spatial non-stationarity of a regression relationship for heterogeneous spatial data distributed over a domain of a complex or irregular shape. Read more about Seminar: Estimation and Inference of Quantile Spatially Varying Coefficient Models over Complicated Domains
Seminar: Estimation for nearest neighbor imputed survey data
Abstract: Sample surveys usually have missing data and have multiple response variables. Nearest neighbor imputation is one procedure used to complete missing records. However, the direct nearest neighbor imputation estimator suffers from a bias that increases as the dimension of the covariate vector increases. In this paper, we construct a regression estimator for the population mean based on the nearest neighbor imputed dataset. We use the regression procedure to reduce the bias in the direct nearest neighbor estimator. Read more about Seminar: Estimation for nearest neighbor imputed survey data
Seminar: Optimizing treatment allocation of a group-randomized clinical trial with a new treatment using existing network meta-analyses
Seminar: estimation and inference of quantile spatially varying coefficient models over complicated domains
Abstract: Regression analysis is frequently used in the analyses of spatial data. In this paper, we propose a flexible quantile spatially varying coefficient model to assess how conditional quantiles of the response depend on covariates, allowing the coefficient function to vary with the spatial locations. The model can be used to explore spatial non-stationarity of a regression relationship for heterogeneous spatial data distributed over a domain of a complex or irregular shape. Read more about Seminar: estimation and inference of quantile spatially varying coefficient models over complicated domains
Seminar: Bayesian Variable Selection for Spatial Linear Mixed Models in Ultra-high Dimensional Settings
Abstract: In agricultural field trial experiments, observations are naturally spatially auto-correlated. Variable selection for these types of data is typically performed using a two-stage procedure by first obtaining spatially adjusted effects and then applying a feature selection method developed for independent observations. Read more about Seminar: Bayesian Variable Selection for Spatial Linear Mixed Models in Ultra-high Dimensional Settings
Seminar: An Explainable Pipeline for Machine Learning with Functional Data
Abstract: Machine learning models are commonly used in applications with an objective of prediction. The complicated algorithms of many of these models, however, make them difficult to interpret. Methods have been proposed to provide insight into these "black-box" models, but there is little research that focuses on the situation when functional data are used as model inputs. Read more about Seminar: An Explainable Pipeline for Machine Learning with Functional Data
Seminar: necessary and sufficient conditions for posterior propriety for generalized linear mixed models
Abstract: Generalized linear mixed models (GLMMs) are often used to analyze non-Gaussian data arising from different studies. In Bayesian GLMMs, the commonly used improper priors may yield undesirable improper posterior distributions. Here we consider the popular improper uniform prior to the regression coefficients and several proper or improper priors including the widely used gamma and power priors on the variance components of the random effects. We derive necessary and sufficient conditions for posterior propriety for Bayesian binomial and Poisson GLMMs. Read more about Seminar: necessary and sufficient conditions for posterior propriety for generalized linear mixed models
Midwest Big Data Summer School
The Midwest Big Data Summer School will held online on May 17-20, 2021. Read more about Midwest Big Data Summer School
Theoretical and Applied Data Science Seminar - Deep learning and its application to remotely sensed data, Dr. Liangxiu Han
Title: Deep learning and its application to remotely sensed data
Location: Zoom Read more about Theoretical and Applied Data Science Seminar - Deep learning and its application to remotely sensed data, Dr. Liangxiu Han
Six Crises One Dozen Opportunities in Public-Stewardship Statistics - John L Eltinge
John L Eltinge, Assistant Director for Research and Methodology, U.S. Census Bureau
Title: Six Crises One Dozen Opportunities in Public-Stewardship Statistics Read more about Six Crises One Dozen Opportunities in Public-Stewardship Statistics - John L Eltinge
Theoretical and Applied Data Science Seminar - Managing Machine Learning Risk: Interpretability and Robustness, Dr. Agus Sudjianto
Title: Managing Machine Learning Risk: Interpretability and Robustness
Location: Zoom Read more about Theoretical and Applied Data Science Seminar - Managing Machine Learning Risk: Interpretability and Robustness, Dr. Agus Sudjianto
Statistical Emulation with Dimension Reduction for Complex Forward Models in Remote Sensing - Emily Kang
Statistical Emulation with Dimension Reduction for Complex Forward Models in Remote Sensing
Zoom Read more about Statistical Emulation with Dimension Reduction for Complex Forward Models in Remote Sensing - Emily Kang
Theoretical and Applied Data Science Seminar - The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks, Dr. Cynthia Rudin
Title: The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks
Location: Zoom Read more about Theoretical and Applied Data Science Seminar - The Extremes of Interpretability in Machine Learning: Sparse Decision Trees, Scoring Systems and Interpretable Neural Networks, Dr. Cynthia Rudin
Estimating means of bounded random variables by betting - Aaditya Ramdas
Speaker: Aaditya Ramdas, Carnegie Mellon University
Title: Estimating means of bounded random variables by betting Read more about Estimating means of bounded random variables by betting - Aaditya Ramdas
Theoretical and Applied Data Science Seminar: Estimating a Covariance Function from Fragments of Functional Data - Aurore Delaigle
Title: Estimating a Covariance Function from Fragments of Functional Data
Zoom Read more about Theoretical and Applied Data Science Seminar: Estimating a Covariance Function from Fragments of Functional Data - Aurore Delaigle
Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data - Georgios Papageorgiou
Lecturer with the Department of Economics, Mathematics & Statistics, Birkbeck, University of London
Title: Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data Read more about Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data - Georgios Papageorgiou
Women in Data Science Ames @ Iowa State University
Theoretical and Applied Data Science Seminar - Valid inferential models and conformal prediction, Ryan Martin
Title: Valid inferential models and conformal prediction.
Location: Zoom Read more about Theoretical and Applied Data Science Seminar - Valid inferential models and conformal prediction, Ryan Martin
Small Area Prediction of Counts under a Spatial Non-Stationary Generalized Linear Mixed Model - Hukum Chandra
Dr. Hukum Chandra
ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India Read more about Small Area Prediction of Counts under a Spatial Non-Stationary Generalized Linear Mixed Model - Hukum Chandra
Design-unbiased statistical learning in survey sampling - Li-Chun Zhang
Dr. Li-Chun Zhang
University of Southampton Read more about Design-unbiased statistical learning in survey sampling - Li-Chun Zhang
Seasonal Warranty Prediction Based on Recurrent Event Data - Bill Meeker
Distinguished Professor Bill Meeker
Iowa State University, Department of Statistics Read more about Seasonal Warranty Prediction Based on Recurrent Event Data - Bill Meeker
Wayne A. Fuller Lecture - Kenneth Prewitt: The Next Census: What's New?
The Next Census: What's New?
Kenneth Prewitt
Carnegie Professor of Public Affairs, Columbia University
Read more about Wayne A. Fuller Lecture - Kenneth Prewitt: The Next Census: What's New?>Computer Science Distinguished Lecture - Ken Goldberg, The New Wave in Robot Grasping
Title: The New Wave in Robot Grasping
Location: Zoom Read more about Computer Science Distinguished Lecture - Ken Goldberg, The New Wave in Robot Grasping
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Laura Miller
Speaker: Laura Miller
Virus and Prion Research Unit, USDA-ARS-NADC
Title: Integrate structural analysis, isoform diversity, and interferon-inductive propensity of ACE2 to predict SARS-CoV-2 susceptibility in vertebrates
Additional details about each talk and speaker will be made available on the Baker Center website. Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Laura Miller
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Eve Wurtele
Speaker: Eve Wurtele
Department of Genetics, Development, and Cell Biology, Iowa State University
Title: The role of ancestry in COVID-19 infection
Additional details about each talk and speaker will be made available on the Baker Center website Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Eve Wurtele
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Walter Moss
Speaker: Walter Moss
Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University
Title: Finding and Folding Functional RNA in SARS-CoV-2
Additional details about each talk and speaker will be made available on the Baker Center website Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Walter Moss
Modeling Sleep Apnea Events Data from Pacifier Users for Improved Diagnosis of OSA - Sujay Datta
University of Akron, Department of Statistics
Modeling Sleep Apnea Events Data from Pacifier Users for Improved Diagnosis of OSA Read more about Modeling Sleep Apnea Events Data from Pacifier Users for Improved Diagnosis of OSA - Sujay Datta
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Yumou Qiu
Speaker: Yumou Qiu
Department of Statistics, Iowa State University
Title: Comparing containment measures by epidemiological effects of COVID-19
Additional details about each talk and speaker will be made available on the Baker Center website Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Yumou Qiu
M-estimation in Low-rank Matrix Factorization: a General Framework - Linglong Kong
University of Alberta, Department of Mathematical and Statistical Science
M-estimation in Low-rank Matrix Factorization: a General Framework Read more about M-estimation in Low-rank Matrix Factorization: a General Framework - Linglong Kong
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Lily Wang
Speaker: Dr. Lily Wang
Department of Statistics, Iowa State University
Title: Nowcasting and Forecasting COVID-19 in the United States
Additional details about each talk and speaker will be made available on the Baker Center website Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Lily Wang
On model-based clustering of skewed matrix and tensor data - Volodymyr Melnykov
Speaker: Dr. Volodymyr Melnykov
University of Alabama, Department of Information Systems, Statistics, and Management Science
On model-based clustering of skewed matrix and tensor data Read more about On model-based clustering of skewed matrix and tensor data - Volodymyr Melnykov
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Jacobson
Speaker: Dan Jacobson
Computational Systems Biology, Biosciences, Oak Ridge National Laboratory
Title: A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm
Additional details about each talk and speaker will be made available on the Baker Center website
Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Dan Jacobson
Improving "*-Seq" -- Applications in Protein-Protein Interactions, Repertoire Sequencing, Allotetraploid Genotyping, and Clustering High-Dimensional Data - Karin Dorman
Speaker: Dr. Karin Dorman
Iowa State University, Department of Statistics
Improving "*-Seq" -- Applications in Protein-Protein Interactions, Repertoire Sequencing, Allotetraploid Genotyping, and Clustering High-Dimensional Data Read more about Improving "*-Seq" -- Applications in Protein-Protein Interactions, Repertoire Sequencing, Allotetraploid Genotyping, and Clustering High-Dimensional Data - Karin Dorman
Baker Center Seminar Series on SARS-CoV2/COVID-19 - Claus Kadelka
Speaker: Claus Kadelka
Department of Mathematics, Iowa State University
Title: A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies
Additional details about each talk and speaker will be made available on the Baker Center website. Read more about Baker Center Seminar Series on SARS-CoV2/COVID-19 - Claus Kadelka
Time Series Clustering and Classification using Topological Data Analysis with applications to Finance - Arnab K Laha
Speaker: Dr. Arnab K Laha
Indian Institute of Management, Ahmedabad, India
Time Series Clustering and Classification using Topological Data Analysis with applications to Finance Read more about Time Series Clustering and Classification using Topological Data Analysis with applications to Finance - Arnab K Laha
Random forests for spatially or serially correlated data - Abhirup Datta
Speaker: Dr. Abhirup Datta
Johns Hopkins University, Department of Biostatistics
Random forests for spatially or serially correlated data Read more about Random forests for spatially or serially correlated data - Abhirup Datta
Methodology to Address Challenges in Small Area Estimation for Erosion - Emily Berg
Speaker: Dr. Emily Berg
Iowa State University, Department of Statistics
Methodology to Address Challenges in Small Area Estimation for Erosion Read more about Methodology to Address Challenges in Small Area Estimation for Erosion - Emily Berg
The Ethical Algorithm - Michael Kearns
Speaker: Dr. Michael Kearns
University of Pennsylvania, Department of Computer and Information Science
The Ethical Algorithm Read more about The Ethical Algorithm - Michael Kearns
Sampling based inference for logistic regression
Speaker:
Dr. HaiYing Wang
University of Connecticut, Department of Statistics
Sampling based inference for logistic regression Read more about Sampling based inference for logistic regression
The Exact Covariance Eigenstructure for AR(1) Processes
Speaker:
Dr. Peter Sherman
ISU Department of Aerospace Engineering and Department of Statistics
The Exact Covariance Eigenstructure for AR(1) Processes Read more about The Exact Covariance Eigenstructure for AR(1) Processes
StegoAppDB: a Steganography Apps Forensics Image Database
Speaker:
Jennifer Newman
Iowa State University, Department of Mathematics
StegoAppDB: a Steganography Apps Forensics Image Database Read more about StegoAppDB: a Steganography Apps Forensics Image Database
Advances in Spatio-Temporal Analysis of Global Oceanographic Data from Argo Profiling Floats
Mikael Kuusela (Department of Statistics and Data Science, Carnegie Mellon University)
Advances in Spatio-Temporal Analysis of Global Oceanographic Data from Argo Profiling Floats Read more about Advances in Spatio-Temporal Analysis of Global Oceanographic Data from Argo Profiling Floats
The Cautious Use of Bayesian Methods in Reliability Data Analyses
William Q. Meeker
Department of Statistics
Center for Nondestructive Evaluation
Iowa State University
The Cautious Use of Bayesian Methods in Reliability Data Analyses Read more about The Cautious Use of Bayesian Methods in Reliability Data Analyses
Analysis of randomized clinical trials with integrated information from real world evidence studies
Shu Yang, NC State
Analysis of randomized clinical trials with integrated information from real world evidence studies
Dept. Seminar - Peihua Qiu
Peihua Qiu, U. Florida
Modeling and Monitoring Spatio-Temporal Disease Incidence Rate Data
Nonignorable Missingness Mechanism Model Can Be Ignored
Jiwei Zhao
State University of New York at Buffalo
Nonignorable Missingness Mechanism Model Can Be Ignored Read more about Nonignorable Missingness Mechanism Model Can Be Ignored
Kernel Nonparametric Overlap-based Syncytial Clustering
Ranjan Maitra
Department of Statistics, Iowa State University
Kernel Nonparametric Overlap-based Syncytial Clustering Read more about Kernel Nonparametric Overlap-based Syncytial Clustering
Dept. Seminar - D. Sen
D. Sen
SAMSI
Monte Carlo algorithms on distributed architectures Read more about Dept. Seminar - D. Sen
Dept. Seminar - Peng Liu
Department Seminar
Peng Liu
Department of Statistics, Iowa State University
Feature Selection in Microbiome Studies Read more about Dept. Seminar - Peng Liu
Dept. Seminar - Lily Wang
Department Seminar
Lily Wang
Department of Statistics, Iowa State University
Statistical Modeling and Inference for Next-Generation Functional Data Analysis Read more about Dept. Seminar - Lily Wang
George Zyskind Memorial Lecture - Jane-Ling Wang
George Zyskind Memorial Lecture
Jane-Ling Wang
University of California, Davis
Functional Snippets: Another form of functional data
Read more about George Zyskind Memorial Lecture - Jane-Ling Wang
Semi-Parametric Quantile Regression Imputation for Missing Response and Covariates Subject to NMAR Nonresponse
Department Seminar
Cindy Yu
Department of Statistics, Iowa State University
Semi-Parametric Quantile Regression Imputation for Missing Response and Covariates Subject to NMAR Nonresponse Read more about Semi-Parametric Quantile Regression Imputation for Missing Response and Covariates Subject to NMAR Nonresponse
Dept. Seminar - ISU Data Mining Cup Project
ISU Data Mining Cup project
Qihao Zhang, Yifan Zhu, Xingche Guo (Stat DMC Team)
A team of Iowa State University graduate students beat nearly 150 teams from 114 universities in 28 countries, bringing home the top prize from the 20th annual Data Mining Cup (2019). Representatives from the winning team will describe their project in this talk.
More on this can be found in the following links:
https://www.news.iastate.edu/news/2019/07/08/data-mining Read more about Dept. Seminar - ISU Data Mining Cup Project
Welcome Back Seminar - Dan Nettleton
Department Seminar
Dan Nettleton
Department Chair
Department of Statistics, Iowa State University
The opening seminar of the semester serves as a “Welcome” event for Statistics students, staff, and faculty. We will introduce some new members of our Statistics community, present student awards, celebrate some successes of the past year, and announce some upcoming opportunities.
Refreshments at 3:45pm in Snedecor 2101. Read more about Welcome Back Seminar - Dan Nettleton
2nd Midwest Statistical Machine Learning Colloquium
It is our pleasure to invite your attendance and participation at the 2nd Midwest Statistical Machine Learning Colloquium, May 13th 2019 at Iowa State University.
Please follow the link below for more information:
https://register.extension.iastate.edu/msmlc/about Read more about 2nd Midwest Statistical Machine Learning Colloquium
A Bayesian approach to identify genes with multiple expression patterns for paired RNA-seq data
Jing Qiu
University of Delaware
A Bayesian approach to identify genes with multiple expression patterns for paired RNA-seq data Read more about A Bayesian approach to identify genes with multiple expression patterns for paired RNA-seq data
The Right Treatment for the Right Patient at the Right Time: Precision Medicine Through Treatment Regimes, SMARTs, and Statistics
Snedecor Memorial Lecture
Marie Davidian
J. Stuart Hunter Distinguished Professor of Statistics
North Carolina State University (NCSU)
The Right Treatment for the Right Patient at the Right Time: Precision Medicine Through Treatment Regimes, SMARTs, and Statistics Read more about The Right Treatment for the Right Patient at the Right Time: Precision Medicine Through Treatment Regimes, SMARTs, and Statistics
Quantile Regression for big data with small memory
Xi Chen
Stern School of Business, New York University
Quantile Regression for big data with small memory Read more about Quantile Regression for big data with small memory
Three-dimensional Radial Visualization of High-dimensional Continuous and Discrete Datasets
Ranjan Maitra
Iowa State University
Three-dimensional Radial Visualization of High-dimensional Continuous and Discrete Datasets Read more about Three-dimensional Radial Visualization of High-dimensional Continuous and Discrete Datasets
Identification of clusters in space based on lattice data
Jun Zhu
University of Wisconsin, Madison
Identification of clusters in space based on lattice data Read more about Identification of clusters in space based on lattice data
What is Brownian motion?
Krishna Athreya
Iowa State University
What is Brownian motion? Read more about What is Brownian motion?
Racial Profiling, Bad Cops, and Police Shootings
Department Seminar
Greg Ridgeway
University of Pennsylvania, Statistics & Criminology
Racial Profiling, Bad Cops, and Police Shootings Read more about Racial Profiling, Bad Cops, and Police Shootings
Dept. Seminar - Xiaoyue (Zoe) Cheng
Xiaoyue (Zoe) Cheng
Department of Mathematics
University of Nebraska at Omaha
Recognition of Crop Alignment for Unmanned Aerial Vehicle Imagery Data Read more about Dept. Seminar - Xiaoyue (Zoe) Cheng
Dept. Seminar - Susan Vanderplas
Susan Vanderplan
Iowa State University
CoNNOR: A Convolutional Neural Network for Outsole Recognition Read more about Dept. Seminar - Susan Vanderplas
Dept. Seminar - Jingshen Wang
Jingshen Wang
University of Michigan
Inference on Treatment Effects after Model Selection Read more about Dept. Seminar - Jingshen Wang
Dept. Seminar - Karen Nielsen
Karen Nielsen
University of Michigan
Statistical Tools for Exploring and Testing Features of Waveform Data Read more about Dept. Seminar - Karen Nielsen
Dept. Seminar - Zhengling Qi
Zhengling Qi
University of North Carolina at Chapel Hill
Learning Optimal Individualized Decision Rules with Risk Control Read more about Dept. Seminar - Zhengling Qi
Dept. Seminar - Susan Vanderplas
Susan Vanderplas
Iowa State University
CoNNOR: A Convolutional Neural Network for Outsole Recognition Read more about Dept. Seminar - Susan Vanderplas
Dept. Seminar - Xin "Henry" Zhang
Xin (Henry) Zhang
Department of Statistics
Florida State University
Covariate-adjusted tensor classification in high-dimensions Read more about Dept. Seminar - Xin "Henry" Zhang
Dept. Seminar - Xueying Tang
Xueying Tang
Columbia University
Analysis of Large Multi-Relational Networks Read more about Dept. Seminar - Xueying Tang
Dept. Seminar - Jon Williams
Jon Williams
University of North Carolina, Chapel Hill
Non-penalized variable selection in high-dimensional settings via generalized fiducial inference Read more about Dept. Seminar - Jon Williams
Dept. Seminar - Lynna Chu
Lynna Chu
Asymptotically distribution-free change-point detection for multivariate and non-Euclidean data Read more about Dept. Seminar - Lynna Chu
Dept. Seminar - Linjun Zhang
Linjun Zhang
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy Read more about Dept. Seminar - Linjun Zhang
Dept. Seminar - Amy Braverman
Amy Braverman
Principal Statistician
Jet Propulsion Laboratory
Uncertainty Quantication for NASA's Orbiting Carbon Observatory-2 Mission Read more about Dept. Seminar - Amy Braverman
Dept. Seminar - Farzad Sabzikar
Farzad Sabzikar
Department of Statistics
Iowa State University
Stochastic processes with semi-long range dependence Read more about Dept. Seminar - Farzad Sabzikar
Dept. Seminar - William Meeker
William Q. Meeker
Department of Statistics
Iowa State University
Applications of the Fractional Random Weight Bootstrap Read more about Dept. Seminar - William Meeker
Dept. Seminar - Giles Hooker
Giles Hooker
Cornell University
Decision Trees and CLT's: Inference and Machine Learning Read more about Dept. Seminar - Giles Hooker
Dept. Seminar - Huilin Li
Huilin Li
New York University, School of Medicine
Statistical Challenges in the Analyses of Human Microbiome Data Read more about Dept. Seminar - Huilin Li
Dept. Seminar - Arka Ghosh
Arka Ghosh
Department of Statistics
Iowa State University
Queueing networks in heavy traffic: History and some recent results
Dept. Seminar - Babette Brumback
Babette Brumback
University of Florida
Model-Based Standardization Using an Outcome Model with Random Effects Read more about Dept. Seminar - Babette Brumback
Dept. Seminar - Lily Wang
Lily Wang
Department of Statistics
Iowa State University
Estimation and Inference for Image-on-Scalar Regression with Application to Imaging Genetics Studies Read more about Dept. Seminar - Lily Wang
Dept. Seminar - Kris De Brabanter
Kris De Brananter
Department of Statistics
Iowa State University
ABSTRACT:
Convergence Rates for Uniform Confidence Intervals Based on Local Polynomial Regression Estimators
We investigate the convergence rates of uniform bias corrected confidence intervals for a smooth curve using local polynomial regression for both the interior and boundary region. Read more about Dept. Seminar - Kris De Brabanter
Dept. Seminar - Qing Li
Qing Li
Industrial & Manufacturing Systems Engr
Iowa State University
Change-Points Detection in the Recurrent-Event Context via Bayesian Inference Read more about Dept. Seminar - Qing Li
Statistics Opening Seminar
Max Morris, Petrutza Caragea, Mark Kaiser
Department of Statistics
Iowa State University
ABSTRACT:
Statistics Opening Seminar
This introductory "seminar" is our official "Welcome" event for new faculty and students in the Department. Professors Morris, Caragea and Kaiser will introduce new Statistics faculty members, present student awards, and describe plans for some professional development workshops for new and returning graduate students.
Dept. Seminar - Irène Gijbels
Irène Gijbels
Department of Mathematics and Leuven Statistics Research Centre, KU Leuven, Belgium
Title: “Nonparametric density and regression estimation in case of measurement errors: a review” Read more about Dept. Seminar - Irène Gijbels
The 1st Midwest Statistical Machine Learning Colloquium
Conference on Predictive Inference and Its Applications
May 7, 2018: 7:30-5:50
May 8, 2018: 7:30-5:00
https://predictiveinference.github.io/ Read more about Conference on Predictive Inference and Its Applications
Dept. Seminar - Gustavo Didier
Gustavo Didier
Tulane University
On multidimensional scaling
Gustavo Didier, Tulane University Read more about Dept. Seminar - Gustavo Didier
PhD Defense Seminar - Seho Park
Speaker: Seho Park
Abstract:
Survey data integration using mass imputation Read more about PhD Defense Seminar - Seho Park
PhD Defense Seminar - Xiaojun Mao
SPEAKER: Xiaojun Mao
ABSTRACT:
Matrix Completion under Low-Rank Missing Mechanism
PhD Defense Seminar - Yeon-Jung Seo
Speaker: Yeon-Jung Seo
Abstract:
Selection and assessment of bivariate Markov random field models Read more about PhD Defense Seminar - Yeon-Jung Seo
Dept. Seminar - Sixia Chen
Sixia Chen
The University of Oklahoma Heath Services Center
Pseudo-population bootstrap methods for imputed survey data Read more about Dept. Seminar - Sixia Chen
PhD Defense Seminar - Andrew Sage
Speaker: Andrew Sage
ABSTRACT
A Robust Residual-Based Approach to Random Forest Regression Read more about PhD Defense Seminar - Andrew Sage
PhD Defense Seminar - Yet Nguyen
Speaker: Yet Nguyen
ABSTRACT:
RNA-seq Differential Expression Analysis for Repeated-measures Data Read more about PhD Defense Seminar - Yet Nguyen
Dept. Seminar - Richard Smith
Richard Smith
Department of Statistics and Operations Research
University of North Carolina, Chapel Hill
INFLUENCE OF CLIMATE CHANGE ON EXTREME WEATHER EVENTS Read more about Dept. Seminar - Richard Smith
Dept. Seminar - Abolfazl Safikhani
Abolfazl Safikhani
Department of Statistics
Columbia University
Joint Structural Break Detection and Parameter Estimation in High-Dimensional Non-Stationary VAR Models
Assuming stationarity is unrealistic in many time series applications. A more realistic alternative is to
allow for piecewise stationarity, where the model is allowed to change at given time points. In this talk, we propose a
three-stage procedure for consistent estimation of both structural change points and parameters of high- Read more about Dept. Seminar - Abolfazl Safikhani
Dept. Seminar - Lan Xue
Lan Xue
Department of Statistics
Oregon State University
Semi-parametric method for non-ignorable missing in longitudinal data using refreshment samples.
Missing data is one of the major methodological problems in longitudinal studies. It not only reduces the sample size, but also can result in biased estimation and inference. It is crucial to correctly understand the missing mechanism and appropriately incorporate it into the estimation and inference procedures. Read more about Dept. Seminar - Lan Xue
Dept. Seminar - Tom Loughin
Tom Loughin
Statistics and Actuarial Science
Simon Fraser University
Adaptively Pruned Random Forests Using Likelihood-Based Trees Read more about Dept. Seminar - Tom Loughin
Dept. Seminar - Farzad Sabzikar
Farzad Sabzikar
Department of Statistics
Iowa State University
Tempered processes: Theory and applications Read more about Dept. Seminar - Farzad Sabzikar
Dept. Seminar - Jan Hannig
Jan Hanning
University of North Carolina at Chapel Hill
Generalized fiducial Inference: A Review Read more about Dept. Seminar - Jan Hannig
PhD Defense Seminar - Nicholas Clark
DATE AND TIME: Friday, March 2, 2018, 2:10 p.m.
PLACE: Snedecor 1109
SPEAKER: Nicholas Clark
ABSTRACT:
Self-Exciting Spatio-Temporal Models for Count Data
Dept. Seminar - Zongwu Cai
Zongwu Cai
Department of Economics
University of Kansas
Models on Testing Predictability of Asset Returns
Testing predictability of asset returns is a cornerstone issue in modern asset pricing
and the related fields. It has been one of the hottest research topics in asset pricing
field in the recent two decades. In this talk, I will combine several of my own papers
(published papers and ongoing projects) on testing predictability of asset returns and Read more about Dept. Seminar - Zongwu Cai
Dept. Seminar - Somak Dutta
Somak Dutta
Department of Statistics
Iowa State University
A Bayesian screening method in ultra-high dimensional settings Read more about Dept. Seminar - Somak Dutta
PhD Defense Seminar - Michael Price
Michael Price
Department of Statistics
Iowa State University
An Investigation of Actuarial Fair Crop Insurance Rates Using Partial Derivatives of Penalized Bivariate Tensor Product B-splines
Plotting Your Date With ggplot2 - Galentine's Day!
A Special Galentine's Day Event!
"Plotting Your Date With ggplot2"
Who: Dr. Heike Hofmann
When: Tuesday, February 13th, 5:15pm
Where: Snedecor 3121
RSVP ASAP: meetup.com/R-Ladies-Ames
More Info Here:
galentines-flyer.pdf Read more about Plotting Your Date With ggplot2 - Galentine's Day!
Dept. Seminar - William Q. Meeker
William G. Meeker
Department of Statistics
Iowa State University
Statistical Intervals Vive La Differénce! Read more about Dept. Seminar - William Q. Meeker
Dept. Seminar - Mark Nieman
Mark Nieman
Department of Political Science
Iowa State University
Strategic Binary Choice Models with Partial Observability
Dept. Seminar - Yumou Qiu
Yumou Qiu
University of Nebraska Lincoln
Threshold selection for covariance learning Read more about Dept. Seminar - Yumou Qiu
Dept. Seminar - Zihuai He
Zihuai He
Columbia University
Inference for statistical interactions under misspecified or high-dimentional main effects Read more about Dept. Seminar - Zihuai He
Dept. Seminar - Xiongtao Dai
Xiongtao Dai
University of California, Davis
Principal Component Analysis for Functional Data on Riemannian Manifolds and Spheres Read more about Dept. Seminar - Xiongtao Dai
Dept. Seminar - Yang Ni
Yang Ni
University of Texas at Austin
Integrative Directed Cyclic Graphical Models with Heterogeneous Samples Read more about Dept. Seminar - Yang Ni
Dept. Seminar - Andee Kaplan
Andee Kaplan
Duke University
A Fast Sampler for Data Simulation from Spatial, and Other, Markov Random Fields Read more about Dept. Seminar - Andee Kaplan
Bob Stephenson Retirement Party
Dept. Seminar - Kris De Brabanter
Kris De Brabanter
Iowa State University
Department of Statistics and Computer Science
Local polynomial regression with correlated errors and unknown correlation structure Read more about Dept. Seminar - Kris De Brabanter
Dept. Seminar - Yimin Xiao
Yimin Xiao
Michigan State University
Joint Estimation of Fractal Indices for Bivariate Gaussian Processes
Multivariate (or vector-valued) stochastic processes are important in probability, statistics and various scientific areas as stochastic models. In recent years, there has been increasing interest in investigating their statistical inference and prediction. Read more about Dept. Seminar - Yimin Xiao
Dept. Seminar - Daniel Sewell
Daniel Sewell
University of Iowa
Simultaneous and temporal autoregressive network models Read more about Dept. Seminar - Daniel Sewell
Dept. Seminar - Subhajit Dutta
Subhajit Dutta
Indian Institute of Technology, Kanpur
Multi-scale Classification using Localized Spatial Depth Read more about Dept. Seminar - Subhajit Dutta
Statistics Seminar Series on Data Science - Tim Hesterberg
Tim Hesterberg
Google, Inc.
Statistics and Big Data at Google
Google lives on data. Search, Ads, YouTube, Maps, ... - they all live on data. I'll tell stories about how we use data, how we're always experimenting to make improvements (yes, this includes your searches), and how we adapt statistical ideas to do things that have never been done before.
BIO:
Read more about Statistics Seminar Series on Data Science - Tim Hesterberg
Lawrence H. Baker Lecture - Bin Yu
Bin Yu
University of California, Berkeley
Three principles of data science: predictability, stability, and computability Read more about Lawrence H. Baker Lecture - Bin Yu
Dept. Seminar - Alejandro Murua
Alejandro Murua
University of Montreal
A Bayesian lasso functional model-based clustering model
We develop a flexible model for the analysis and clustering of complete or sparse time-course data. Read more about Dept. Seminar - Alejandro Murua
Dept. Seminar - Sanvesh Srivastava
Sanvesh Srivastava
University of Iowa
Wasserstein barycenter and its application in distributed Bayesian inference
Dept. Seminar - Yehua Li
Yehua Li
Iowa State University
Department of Statistics
Semiparametric Regression and Nonparametric Hypothesis Tests for Functional Data Read more about Dept. Seminar - Yehua Li
Dept. Seminar - Petrutza Caragea
Petrutza Caragea
Iowa State University
Department of Statistics
Modeling Space Weather Relationships using Multiscale Dynamic Linear Models Read more about Dept. Seminar - Petrutza Caragea
Dept. Seminar - David Matteson
David Matteson
Department of Statistical Science
Cornell University
Sparse Identification and Estimation of High-Dimensional Vector AutoRegressive Moving Averages Read more about Dept. Seminar - David Matteson
Dept. Seminar - Chinmay Hegde
Chinmay Hegde
Electrical and Computer Engineering
Iowa State University
Fast(er) Algorithms for Machine Learning in High Dimensions Read more about Dept. Seminar - Chinmay Hegde
Dept. Seminar - Max Morris
Max Morris
Iowa State University Department of Statistics
Statistics Opening Seminar
This introductory "seminar" is our official "Welcome" event for new faculty and students in the Department. Professors Morris, Caragea and Kaiser will introduce new Statistics faculty members, present student awards, and describe plans for some professional development workshops for new and returning graduate students.
Refreshments at 3:45pm in Snedecor 2101. Read more about Dept. Seminar - Max Morris
Fuller Lecture - Donna Spiegelman
Donna Spiegelman
Harvard University
Measurement error: from Fuller to the future Read more about Fuller Lecture - Donna Spiegelman
Dept. Seminar - Mikyoung Jun
Mikyoung Jun
Texas A&M University
Covariance models for spatial data on a global scale Read more about Dept. Seminar - Mikyoung Jun
Dept. Seminar - Steve Lund
Steve Lund
National Institute of Standards and Technology
Assessing High Dimensional Evidence: Scores, Probability, and Scientific Validity Read more about Dept. Seminar - Steve Lund
Dept. Seminar - Danica Ommen
Danica Ommen
South Dakota State University
Approximate Solutions to the Forensic Identification of Source Problems Read more about Dept. Seminar - Danica Ommen
Dept. Seminar - John Sall, JMP
John Sall
JMP
From Big Data to Big Statistics
Now that we have Big Data we have new challenges. When big data is wide, there are too many things to look at. When we screen for just the big effects, we need to worry about selection bias. When we graph significance, we have the change scales. When you have tall data, everything is significant, but many effects are too small to care about. When you have holes and bumps all over your data, you need something automatic to adapt to them. All this needs to be resolved in a Big Statistics analytic work flow. Read more about Dept. Seminar - John Sall, JMP
Dept. Seminar - Marina Vannucci
Marina Vannucci
Rice University
Bayesian Variable Selection Methods for Large-scale Genomic and Neuroimaging Data
There is now a huge literature on methods for variable selection that use spike-and-slab priors. Such methods, in particular, have been quite successful for applications in a variety of different fields.
High-throughput genomics and neuroscience are two of such examples. Read more about Dept. Seminar - Marina Vannucci
Dept. Seminar - Chris Saunders
Chris Saunders
South Dakota State University
Using Subsampling to Investigate the Dependency of Match Probabilities on the Size of Writing Samples Read more about Dept. Seminar - Chris Saunders
Dept. Seminar - Jean Opsomer
Jean Opsomer
Professor
Department of Statistics
Colorado State University
Survey estimation of domain means that respect natural orderings Read more about Dept. Seminar - Jean Opsomer
Dept. Seminar - Ranjan Maitra
Ranjan Maitra
Dept. of Statistics
Iowa State University
FAST Adaptive Smoothed Thresholding for Improved Activation Detection in Low-Signal fMRI
Dept. Seminar- Naomi Kaplan
Naomi Kaplan,
Hebrew University, Israel
Statistical Methods for Evaluating Forensic Evidence: The Case of Shoe Prints Read more about Dept. Seminar- Naomi Kaplan
Dept. Seminar - David Miller
David Miller:
Integrated Statistics, Woods Hole, MA,
Centre for Research into Ecological and Environmental Modelling & School of Mathematics and Statistics, University of St Andrews, Scotland
Woods Hole Oceanographic Institution, Woods Hole, MA
Where the whale-things are: Distribution, detectability and availability modelling for cetacean populations. Read more about Dept. Seminar - David Miller
R-Ladies Ames Meetup
Webscraping with tidyverse Packages in R Read more about R-Ladies Ames Meetup
Dept. Seminar - Soumik Sarkar
Soumik Sarkar
Assistant Professor
Department of Mechanical Engineering Iowa State University
Spatiotemporal Graphical Modeling for Complex Cyber-Physical Systems Read more about Dept. Seminar - Soumik Sarkar
Dept. Seminar - Yumou Qiu
Yumou Qiu
Asst. Professor
University of Nebraska-Lincoln
Lincoln, NE
Statistical Inference for Large Precision Matrices with Applications to Brain Connectivity Read more about Dept. Seminar - Yumou Qiu
Jin Tian, Dept. Seminar
Jin Tian
Associate Professor
Computer Science
Iowa State University
Ames, Iowa
Inference with Selection Bias in Causal Graphical Models Read more about Jin Tian, Dept. Seminar
Dabao Zhang, Dept. Seminar
Dabao Zhang
Professor
Department of Statistics
Purdue University
West Lafayette. Indiana
A Novel Approach to Reveal Whole Systems of Gene-Gene Regulations Read more about Dabao Zhang, Dept. Seminar
Hongyuan Cao, Dept. Seminar
Hongyuan Cao
Assistant Professor
Department of Statistics
University of Missouri
Columbia, Missouri
Change-point estimation: another look at multiple testing problems
We consider large scale multiple testing for data that have locally
clustered signals. With this structure, we apply techniques from
change-point analysis and propose a boundary detection algorithm so that
the clustering information can be utilised. Consequently the precision of Read more about Hongyuan Cao, Dept. Seminar
Lan Wang, Dept. Seminar
Lan Wang
Professor
Department of Statistics
University of Minnesota
Minneapolis, Minnesota
Estimation and Inference of Quantile Regression Under Biased Sampling Read more about Lan Wang, Dept. Seminar
Lan Zhu, Dept. Seminar
Lan Zhu
Associate Professor
Department of Statistics
Oklahoma State University
Stillwater, Oklahoma
A Powerful Statistical Method for Identifying Genes under Positive Selection from the Human Genome Read more about Lan Zhu, Dept. Seminar
Vivek Roy, Dept. Seminar
Vivek Roy
Professor
Department of Statistics
Iowa State University
Ames, Iowa
Standard errors for generalized importance sampling estimators Read more about Vivek Roy, Dept. Seminar
Dennis Lock, PhD Defense Seminar
Using the Random Forest to Estimate In-Game Win Probability
Bill Meeker, Dept. Seminar
Bill Meeker
Distinguished Professor
Department of Statistics
Iowa State University
Ames, Iowa
Service Life Prediction of Field-Exposed Units Based on Laboratory Accelerated Degradation Test Data Read more about Bill Meeker, Dept. Seminar
Joe Guinness, Dept. Seminar
Joe Guinness
Assistant Professor
Department of Statistics
North Carolina State University
Raleigh, North Carolina
Permutation Methods for Sharpening Gaussian Process Approximations Read more about Joe Guinness, Dept. Seminar
Zhengyuan Zhu, Dept. Seminar
Zhengyuan Zhu
Professor
Department of Statistics
Iowa State University
Ames, Iowa
Non-Stationary Spatial Models: Some Theory and Applications Read more about Zhengyuan Zhu, Dept. Seminar
Quentin Brummet, Dept. Seminar
Quentin Brummet
Chief, Experiments and Innovation Branch
Center for Administrative Records Research and Applications
U.S. Census Bureau
Administrative Records Use at the US Census Bureau Read more about Quentin Brummet, Dept. Seminar
Sharon Lohr, Dept. Seminar
Sharon Lohr
Vice President
Westat
Rockville, MD
The Essential Survey Statistician Read more about Sharon Lohr, Dept. Seminar
Jarad Niemi, Dept. Seminar
Jarad Niemi
Assistant Professor
Department of Statistics
Iowa State University
Ames, Iowa
Fully Bayesian analysis of RNAseq data for gene expression heterosis detection Read more about Jarad Niemi, Dept. Seminar
Xiaoke Zhang, Dept. Seminar
Xiaoke Zhang
Assistant Professor
Department of Statistics
University of Delaware
Newark, Delaware
https://sites.google.com/a/udel.edu/xkzhang/home
A Systematic Study on Weighing Schemes for Functional Data Read more about Xiaoke Zhang, Dept. Seminar
Zhengjun Zhang, Dept. Seminar
Zhengjun Zhang
Professor
Department of Statistics
University of Wisconsin
Madison, Wisconsin
ATM: Autoregressive Tail-index Model for Financial Time Series Read more about Zhengjun Zhang, Dept. Seminar
Opening Statistics Seminar, Max Morris
This introductory “seminar” is our official “Welcome” event for new students in the Department. Professors Morris, Caragea, and Kaiser will introduce the new Statistics students, present student awards, and present the results of last year’s survey on professional development workshops for graduate students Read more about Opening Statistics Seminar, Max Morris
Statistics Opening Seminar, Max Morris
(Dept Seminar) Max Morris, Department of Statistics, Iowa State University, Ames
This introductory “seminar” is our official “Welcome” event for new students in the Department. Professors Morris, Caragea, and Kaiser will introduce the new Statistics students, present student awards, and present the results of last year’s survey on professional development workshops for graduate students. Read more about Statistics Opening Seminar, Max Morris
Guillermo Basulto-Elias, Computation of kernel deconvolution density estimators
In many areas of application, like medical sciences, variables of interest are not directly observable and may be measured only in the presence of contaminating errors. These cases are often referred as ``measurement error problems.'' Kernel deconvolution density estimation (KDDE) is an approach for handling such measurement errors, which consists of separating out and estimating the density of a target variable from observations blurred by additive errors. The method involves an adaptation of kernel density estimation using the Fourier inversion theorem. Read more about Guillermo Basulto-Elias, Computation of kernel deconvolution density estimators
Prediction and Inference with Missing Data in Patient Alert Systems
Prediction and Inference with Missing Data in Patient Alert Systems
Read more about Prediction and Inference with Missing Data in Patient Alert Systems
Efficient Computing Workflow Group
Efficient Computing Workflow Group
Date: | Friday, February 05 |
Time: | 2:00 pm -- 3:00 pm |
Place: | Snedecor 2102 |
Speaker: | Ian Mouzon and Evan "Pete" Walsh, Department of Statistics, Iowa State University |
Abstract:
We are excited to announce the formation of a new working group, the Efficient Computing Workflow group. Read more about Efficient Computing Workflow Group
Multiple Testing with Heterogeneous Multinomial Distributions
Multiple Testing with Heterogeneous Multinomial Distributions
Read more about Multiple Testing with Heterogeneous Multinomial Distributions
Some recent topics on informative sampling
Some recent topics on informative sampling
Using the geomnet Package: Visualizing African Slave Trade, 1514 - 1866,
Using the geomnet Package: Visualizing African Slave Trade, 1514 - 1866
Read more about Using the geomnet Package: Visualizing African Slave Trade, 1514 - 1866,
Multilevel Functional Data Analysis: Modeling and Testing
07 December 4:10 pm, Snedecor 3105
Multilevel Functional Data Analysis: Modeling and Testing, (Dept Seminar) Yuhang Xu, Department of Statistics, Iowa State University, Ames Read more about Multilevel Functional Data Analysis: Modeling and Testing
Goodness of fit tests for spatial Markov random fields
04 December 3:10 pm, Snedecor 2113
Goodness of fit tests for spatial Markov random fields, (Dept Seminar) Andee Kaplan, Department of Statistics, Iowa State University, Ames Read more about Goodness of fit tests for spatial Markov random fields
Bayesian Screening for Group Differences in High-Throughput Data
16 November 4:10 pm, Snedecor 3105
Bayesian Screening for Group Differences in High-Throughput Data, (Dept Seminar) Eric Lock, Department of Biostatistics, University of Minnesota, Minneapolis Read more about Bayesian Screening for Group Differences in High-Throughput Data
Graphing better Impulse Response Functions for discrete-time linear models
11 November 4:10 pm, Snedecor 1109
Graphing better Impulse Response Functions for discrete-time linear models, (Other) Gray Calhoun, Department of Economics, Iowa State University, Ames Read more about Graphing better Impulse Response Functions for discrete-time linear models
A Ballooned Beta-Logistic Model with a Bioassay Application
02 November 4:10 pm, Snedecor 3105
A Ballooned Beta-Logistic Model with a Bioassay Application, (Dept Seminar) Nancy Flournoy, Department of Statistics, University of Missouri Read more about A Ballooned Beta-Logistic Model with a Bioassay Application
Fractional Factorial Designs with Clear Two-Factor Interactions
26 October 4:10 pm, Snedecor 3105
Fractional Factorial Designs with Clear Two-Factor Interactions, (Dept Seminar) Huaiqing Wu, Department of Statistics, Iowa State University, Ames Read more about Fractional Factorial Designs with Clear Two-Factor Interactions
Design and Analysis of Definitive Screening Experiments (Zyskind Memorial Lecture)
19 October 4:10 pm, Snedecor 3105
Design and Analysis of Definitive Screening Experiments (Zyskind Memorial Lecture), (Dept Seminar) Christopher J. Nachtsheim, Frank A. Donaldson Chair of Operations Management, Carlson School of Management, University of Minnesota, Minneapolis Read more about Design and Analysis of Definitive Screening Experiments (Zyskind Memorial Lecture)
Experimental designs for multiple responses with different models
16 October 1:00 pm, Snedecor 2113
Experimental designs for multiple responses with different models, (Dept Seminar) Wilmina Marget, Department of Statistics, Iowa State University, Ames Read more about Experimental designs for multiple responses with different models
Statisticians at Work: Inspiration, Aspiration, Ambition
13 October 7:30 pm, Durham 0171
Statisticians at Work: Inspiration, Aspiration, Ambition, (Dept Seminar) Jeff Wu, Coca-Cola Chair in Engineering Statistics, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta Read more about Statisticians at Work: Inspiration, Aspiration, Ambition
A Fresh Look at Effect Aliasing and Interactions: Some New Wine in Old Bottle
12 October 4:10 pm, Morrill Hall 2019
A Fresh Look at Effect Aliasing and Interactions: Some New Wine in Old Bottle, (Dept Seminar) Jeff Wu, Coca-Cola Chair in Engineering Statistics, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta Read more about A Fresh Look at Effect Aliasing and Interactions: Some New Wine in Old Bottle
Map Representation of Polling Data
Map Representation of Polling Data
Date: | Thursday, October 09 |
Time: | 3:30 pm -- 4:30 pm |
Place: | 2624 Howe Hall |
Speaker: | Barret Schloerke |
Abstract:
Survey Research Services at CSSM
Survey Research Services at CSSM.
Statistics in the Era of Big Data: Genetics and Genomics
05 October 4:10 pm, Alliant Energy-Lee Auditorium, Howe Hall
Statistics in the Era of Big Data � Genetics and Genomics, (Dept Seminar) Robert Gentleman, 23andMe Read more about Statistics in the Era of Big Data: Genetics and Genomics
Finance Paper Discussions
Finance Paper Discussions
Computationally Efficient Estimation of False Discovery Rate Using Sequential Permutation p-Values
Computationally Efficient Estimation of False Discovery Rate Using Sequential Permutation p-Values
Using Accelerated Life Tests Results to Predict Product Field Reliability
Using Accelerated Life Tests Results to Predict Product Field Reliability
Read more about Using Accelerated Life Tests Results to Predict Product Field Reliability
Modeling Outlying Labs in Inter-Laboratory Studies
Modeling Outlying Labs in Inter-Laboratory Studies
Read more about Modeling Outlying Labs in Inter-Laboratory Studies
Web Panel Surveys
Web Panel Surveys
The relationship between Put and Call options
The relationship between Put and Call options
Read more about The relationship between Put and Call options
Hidden Markov Random Fields: Spatial Random Effects for Lattice Data
Hidden Markov Random Fields: Spatial Random Effects for Lattice Data
Read more about Hidden Markov Random Fields: Spatial Random Effects for Lattice Data
Relating Self-report and Accelerometer Physical Activity with Application to NHANES 2003-2004
Relating Self-report and Accelerometer Physical Activity with Application to NHANES 2003-2004
Date: | Monday, September 15 |
Time: | 3:10 pm -- 4:00 pm |
Place: | Carver 298 |
Speaker: | Nicholas Beyler |
Abstract:
Nicholas Beyler (presenting), Sarah Nusser, Wayne Fuller, Gregory Welk
Iowa State University
Local Structure Graph Models, Parameter Centering & Higher-Order Dependence,
Local Structure Graph Models, Parameter Centering & Higher-Order Dependence
Read more about Local Structure Graph Models, Parameter Centering & Higher-Order Dependence,
Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Read more about Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Explorations of the lineup protocol for visual inference: application to high dimension, low sample size problems and metrics to assess the quality
Explorations of the lineup protocol for visual inference: application to high dimension, low sample size problems and metrics to assess the quality
Generalized Method of Moments Estimator Based On Semiparametric Quantile Regression Imputation
Generalized Method of Moments Estimator Based On Semiparametric Quantile Regression Imputation
A week of R
A week of R
A frequency domain empirical likelihood for estimation and testing of spatial covariance structure
A frequency domain empirical likelihood for estimation and testing of spatial covariance structure
Local Structure Graph Models, Parameter Centering & Higher-Order Dependence
Local Structure Graph Models, Parameter Centering & Higher-Order Dependence
Read more about Local Structure Graph Models, Parameter Centering & Higher-Order Dependence
Local Structure Graph Models, Parameter Centering & Higher-Order Dependence Date: Thursday, July 31 Time: 2:00 pm -- 3:00 pm Place: 2113 Snedecor Hall Speaker: Emily Casleton Abstract: This talk describes a new class of models for random graphs or network
Explorations of the lineup protocol for visual inference: application to high dimension, low sample size problems and metrics to assess the quality
Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Read more about Detection of Rare and Faint Signals on High-Dimensional Count Distribution
Generalized Method of Moments Estimator Based On Semiparametric Quantile Regression Imputation
Generalized Method of Moments Estimator Based On Semiparametric Quantile Regression Imputation
Hierarchical Poisson Models for Spatial Count Data: A Closer Look
Hierarchical Poisson Models for Spatial Count Data: A Closer Look
Read more about Hierarchical Poisson Models for Spatial Count Data: A Closer Look
Random Matrix Theory and Covariance Matrix Estimation
Random Matrix Theory and Covariance Matrix Estimation
Read more about Random Matrix Theory and Covariance Matrix Estimation
A practical bootstrap method for testing hypotheses from survey data
A practical bootstrap method for testing hypotheses from survey data
Read more about A practical bootstrap method for testing hypotheses from survey data
Semiparametric estimation of spectral density function for irregular spatial data
Semiparametric estimation of spectral density function for irregular spatial data
Read more about Semiparametric estimation of spectral density function for irregular spatial data
A Bayesian Hierarchical Topographic Clustering Method Motivated by the Self-Organizing Map
A Bayesian Hierarchical Topographic Clustering Method Motivated by the Self-Organizing Map
Sensitive and precise detection of somatic changes of the class I HLA loci using exome-capture sequencing
Sensitive and precise detection of somatic changes of the class I HLA loci using exome-capture sequencing
Kernal Smoothed VIX
Kernal Smoothed VIX
Relative fixed-width stopping rules for Markov chain Monte Carlo simulations
Relative fixed-width stopping rules for Markov chain Monte Carlo simulations
Read more about Relative fixed-width stopping rules for Markov chain Monte Carlo simulations
R workshop: knitting documents in R
R workshop: knitting documents in R
Causal mediation analysis under the presence of unmeasured confounder
Causal mediation analysis under the presence of unmeasured confounder
Read more about Causal mediation analysis under the presence of unmeasured confounder
Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data
Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data
Structure Learning in Bayesian Networks & Session Analysis for Professional Social Networks
Structure Learning in Bayesian Networks & Session Analysis for Professional Social Networks
JRC Experience with Area Frame Sampling
JRC Experience with Area Frame Sampling
Date: | Wednesday, April 02 |
Time: | 4:10 pm -- 5:00 pm |
Place: | Snedecor 3105 |
Speaker: | Jacques Delince, European Commission Joint Research Centre, IPTS - Agriculture and Life Sciences in the Economy, Seville, Spain |
Abstract:
WAYNE FULLER LECTURE
Innovative Approaches for Measuring and Analyzing Daily Patterns of Health Risk Behaviors
Innovative Approaches for Measuring and Analyzing Daily Patterns of Health Risk Behaviors
Bayesian Variable Selection in the Presence of Multicollinearity
Bayesian Variable Selection in the Presence of Multicollinearity
Read more about Bayesian Variable Selection in the Presence of Multicollinearity
Will the Real Steve Fienberg Please Stand Up: A Bayesian Approach to Graphical Record Linkage*
Will the Real Steve Fienberg Please Stand Up: A Bayesian Approach to Graphical Record Linkage*
R workshop: shiny applets
R workshop: shiny applets
Nonparametric Bayesian Models to Handle Nonresponse in Large Scale Panel Studies with Refreshment Samples
Nonparametric Bayesian Models to Handle Nonresponse in Large Scale Panel Studies with Refreshment Samples
Survival Prediction and Variable Selection with Simultaneous Shrinkage and Grouping Priors for Gene Expression Microarray Data
Survival Prediction and Variable Selection with Simultaneous Shrinkage and Grouping Priors for Gene Expression Microarray Data
R workshop: Advanced graphics in R
R workshop: Advanced graphics in R
Transitivity, scale-invariance, and rank tests
Transitivity, scale-invariance, and rank tests
Read more about Transitivity, scale-invariance, and rank tests
Regularized Semiparametric Functional Linear Regression
Regularized Semiparametric Functional Linear Regression
Read more about Regularized Semiparametric Functional Linear Regression
Fiber Direction Estimation in Diffusion MRI
Fiber Direction Estimation in Diffusion MRI
Covariance assisted screening and estimation
Covariance assisted screening and estimation
Read more about Covariance assisted screening and estimation
On the Identifiability of Q-matrix Based CDM's
On the Identifiability of Q-matrix Based CDM's
Read more about On the Identifiability of Q-matrix Based CDM's
ERGM with unknown normalizing constant
ERGM with unknown normalizing constant
Big Data: The End of Sampling As We Know It?
Big Data: The End of Sampling As We Know It?
Read more about Big Data: The End of Sampling As We Know It?
Matrix-free computations for Gaussian Markov random fields and related spatial processes
Matrix-free computations for Gaussian Markov random fields and related spatial processes
Recursive nonparametric estimation for time series
Recursive nonparametric estimation for time series
Read more about Recursive nonparametric estimation for time series
Aspects of Long-Range First-Passage Percolation
Aspects of Long-Range First-Passage Percolation
Read more about Aspects of Long-Range First-Passage Percolation
Bayesian Inference for a New Class of Distributions on Equivalence Classes of 3-D Orientations With Applications to Materials Science
Bayesian Inference for a New Class of Distributions on Equivalence Classes of 3-D Orientations With Applications to Materials Science
Estimation of the Central Orientation for Rotation Data
Estimation of the Central Orientation for Rotation Data
Read more about Estimation of the Central Orientation for Rotation Data
Review of Soil Erosion Analysis in NRI
Review of Soil Erosion Analysis in NRI
Evaluating the Impact of Nonsampling Errors on Erosion Estimates for the Conservation Effects Assessment Project
Evaluating the Impact of Nonsampling Errors on Erosion Estimates for the Conservation Effects Assessment Project
Evaluating Errors in Administrative Data
Evaluating Errors in Administrative Data
Date: | Friday, March 15 |
Time: | 12:00 pm -- 1:00 pm |
Place: | Snedecor 2113 |
Speaker: | Michael Price, Department of Statistics, ISU |
Abstract:
There is increasing interest in the use of administrative data as input to the estimation process for survey data. Read more about Evaluating Errors in Administrative Data
Propensity score adjustment under non-ignorable non-response using information from paradata
Propensity score adjustment under non-ignorable non-response using information from paradata
Quantifying Recall and Processing Error when Utilizing the Compendium of Physical Activities in Physical Activity Recall Surveys, A Disucssion
Quantifying Recall and Processing Error when Utilizing the Compendium of Physical Activities in Physical Activity Recall Surveys, A Disucssion
Total Survey Error
Total Survey Error
Abstract:The survey working group will continue to discuss total survey error. We will meet on Friday 2/22 at 12:00 in Sned 2113. |
Total Survey Error
Total Survey Error
Historical Graphics
Historical Graphics
Survey Working Group
Survey Working Group
Date: | Friday, February 01 |
Time: | 12:00 pm -- 1:00 pm |
Place: | Snedecor 2113 |
Speaker: |
Getting Started with Shiny
Getting Started with Shiny
Date: | Wednesday, January 30 |
Time: | 3:10 pm -- 4:00 pm |
Place: | Snedecor 2113 |
Speaker: | Carson Sievert, Department of Statistics, ISU |
Abstract:
Data-driven web applications are quickly gaining traction as a reliable vehicle for Read more about Getting Started with Shiny
Total Survey Error
Total Survey Error
ASA Data Expo Challenge
ASA Data Expo Challenge
Date: | Wednesday, January 23 |
Time: | 3:10 am -- 4:00 pm |
Place: | 2113 Snedecor |
Speaker: | Heike Hofmann, Department of Statistics, Iowa State U |
Abstract:
Welcome to Spring Semester Statistical Graphics Group Meeting
Resolving Isoform Expression using Digital Gene Expression Data
The advent of ultra-high throughput sequencing technology has made it possible to directly sequence large numbers of mRNA fragments, obtaining a direct measure of mRNA abundance. Restriction enzyme fragmentation reliably produces a single sequenced fragment per mRNA, providing a direct measure of digital gene expression from tag counts. However, genes in complex organisms may encode multiple mRNAs, called isoforms which result in different proteins. Since each restriction site can belong to multiple isoforms, the counts must be partitioned among the is Read more about Resolving Isoform Expression using Digital Gene Expression Data
V-uniform Ergodicity for State-dependent Single Class Queueing Networks*
Analysis of Window-Observation Recurrence Data
Date: | Thursday, April 15 |
Time: | 8:00 am -- 9:00 am |
Place: | 2113 Snedecor |
Speaker: | Angela Zuo, Department of Statistics, ISU |
Abstract:
Read more about Analysis of Window-Observation Recurrence Data>Antedependence models for longitudinal data
Date: | Monday, April 12 |
Time: | 4:10 pm -- 5:00 pm |
Place: | 3105 Snedecor |
Speaker: | Dale Zimmerman, Dept. Statistics & Actuarial Science, U of IA, IA City |
Abstract:
Probabilistic Studies of Different Investment Strategies
Date: | Monday, April 12 |
Time: | 10:30 am -- 11:30 am |
Place: | 2113 Snedecor |
Speaker: | Ling Huang, Department of Statistics, Iowa State U |
Abstract:
Read more about Probabilistic Studies of Different Investment Strategies>A Comprehensive Analysis for Multiple Genomic Data Types via Bayesian Path Analysis
A Comprehensive Analysis for Multiple Genomic Data Types via Bayesian Path Analysis, (Bioinformatics and Genetic Statistics) Steve Lund, Department of Statistics, Iowa State University Read more about A Comprehensive Analysis for Multiple Genomic Data Types via Bayesian Path Analysis