Seminar Notice

Statistical Laboratory
Iowa State University
 
DATE AND TIME: Wednesday, January 19, 2005, 4:10 p.m.
 
PLACE: 319 Snedecor
 
SPEAKER: Daniel Nordman, Department of Statistics, University of Wisconsin – La Crosse
                                            
TITLE: Developing Empirical Likelihood Under Long-Range Dependence
 

ABSTRACT

 
This talk discusses the development of empirical likelihood (EL) methods for linear time series which exhibit long-range dependence or strong forms of dependence. For weakly dependent or short-range dependent time processes, Kitamura~(1997) has proposed a version of EL (blockwise EL) based on data blocking techniques that have successfully lead to other nonparametric likelihoods, like the block bootstrap.
 
This talk explains why blockwise EL, like the block bootstrap (Lahiri, 1993), does not extend easily to long-range dependent time processes. One problem is that blockwise EL ratios involve “`block adjustment” factors to ensure limiting chi-square distributions and these adjustments are simple to formulate under weak dependence but quite complicated under strong dependence.
 
As an alternative to data blocking, we introduce a new version of empirical likelihood based on the periodogram (a data transformation) and spectral estimating equations.  Under both weak dependence and strong forms of dependence, the method results in likelihood ratios which can be used to build nonparametric, asymptotically correct confidence regions for spectral parameters like autocorrelations and Whittle parameters.
 
COFFEE:    3:45 p.m., 104 Snedecor Hall