Farzad Sabzikar
Department of Statistics
Iowa State University

Tempered processes: Theory and applications 

Tempered processes are stationary time series that have a semi-long memory property in the sense that the autocovariogram of the process resembles that of a long memory model for moderate lags but eventually diminishes exponentially fast according to the presence of a decay factor governed by a tempering parameter. When the tempering parameter is sample size dependent, the resulting class of processes admits a wide range of behavior that includes both long memory, semi-long memory, and short memory processes. Several examples from finance, geophysics and turbulence illustrate the utility of the tempered processes.  The asymptotic theory for near integrated random processes and some associated regressions when the errors are tempered linear processes will be discussed (if time is permitted).

Refreshments at 3:45pm in Snedecor 2101.