Translator Disclaimer
May 2019 Towards a general theory for nonlinear locally stationary processes
Rainer Dahlhaus, Stefan Richter, Wei Biao Wu
Bernoulli 25(2): 1013-1044 (May 2019). DOI: 10.3150/17-BEJ1011

Abstract

In this paper, some general theory is presented for locally stationary processes based on the stationary approximation and the stationary derivative. Laws of large numbers, central limit theorems as well as deterministic and stochastic bias expansions are proved for processes obeying an expansion in terms of the stationary approximation and derivative. In addition it is shown that this applies to some general nonlinear non-stationary Markov-models. In addition the results are applied to derive the asymptotic properties of maximum likelihood estimates of parameter curves in such models.

Citation

Download Citation

Rainer Dahlhaus. Stefan Richter. Wei Biao Wu. "Towards a general theory for nonlinear locally stationary processes." Bernoulli 25 (2) 1013 - 1044, May 2019. https://doi.org/10.3150/17-BEJ1011

Information

Received: 1 April 2017; Revised: 1 November 2017; Published: May 2019
First available in Project Euclid: 6 March 2019

zbMATH: 07049398
MathSciNet: MR3920364
Digital Object Identifier: 10.3150/17-BEJ1011

Rights: Copyright © 2019 Bernoulli Society for Mathematical Statistics and Probability

JOURNAL ARTICLE
32 PAGES

This article is only available to subscribers.
It is not available for individual sale.
+ SAVE TO MY LIBRARY

SHARE
Vol.25 • No. 2 • May 2019
Back to Top