Asymptotic theory for regression models with fractional local to unity root errors
Statistics Theory
2020-02-25 v1 Statistics Theory
Abstract
This paper develops the asymptotic theory for parametric and nonparametric regression models when the errors have a fractional local to unity root (FLUR) model structure. FLUR models are stationary time series with semi-long range dependence property in the sense that their covariance function 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 noncentrality parameter. When this parameter is sample size dependent, the asymptotic normality for these regression models admit a wide range of stochastic processes with behavior that includes long, semi-long, and short memory processes.
Cite
@article{arxiv.2002.09753,
title = {Asymptotic theory for regression models with fractional local to unity root errors},
author = {Farzad Sabzikar and Kris De Brabanter},
journal= {arXiv preprint arXiv:2002.09753},
year = {2020}
}