Asymptotic Theory for Near Integrated Processes Driven by Tempered Linear Processes

Farzad Sabzikar, Department of Statistics, Iowa State University, USA

In this talk, we establish asymptotic theory for near-integrated random processes and associated regressions including the score function in more general settings where the errors are tempered linear processes. 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. The limit results relate to tempered fractional processes that include tempered fractional Brownian motion and tempered fractional diffusion process of the second kind.

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• MSUStatSymposium2018@stt.msu.edu
• Michigan State University
  Department of Statistics and Probability
  Room C413 Wells Hall
  619 Red Cedar Road
  East Lansing, MI 48824