Geometric ergodicity and conditional self-weighted M-estimator of a GRCAR(p) model with heavy‐tailed errors

Li, Xiaoyan and Pan, Jiazhu and Song, Anchao (2023) Geometric ergodicity and conditional self-weighted M-estimator of a GRCAR(p) model with heavy‐tailed errors. Journal of Time Series Analysis, 44 (4). pp. 418-436. ISSN 0143-9782 (https://doi.org/10.1111/jtsa.12680)

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Abstract

We establish the geometric ergodicity for general stochastic functional autoregressive (linear and nonlinear) models with heavy-tailed errors. The stationarity conditions for a generalized random coefficient autoregressive model (GRCAR($p$)) are presented as a corollary. And then, a conditional self-weighted M-estimator for parameters in the GRCAR($p$) is proposed. The asymptotic normality of this estimator is discussed by allowing infinite variance innovations. Simulation experiments are carried out to assess the finite-sample performance of the proposed methodology and theory, and a real heavy-tailed data example is given as illustration.

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• Item metadata

  Item type:	Article
  ID code:	83843
  Dates:	Date Event 31 July 2023 Published 19 January 2023 Published Online 13 January 2023 Accepted
  Subjects:	Science > Mathematics
  Department:	Faculty of Science > Mathematics and Statistics
  Depositing user:	Pure Administrator
  Date deposited:	26 Jan 2023 11:05
  Last modified:	11 Apr 2024 02:36
  URI:	https://strathprints.strath.ac.uk/id/eprint/83843