Strong Consistency for the Conditional Self-weighted M Estimator of GRCA(p) Models

Chi Yao, Wei Yu and Xuejun Wang ()
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Chi Yao: Anhui University
Wei Yu: Anhui University
Xuejun Wang: Anhui University

Methodology and Computing in Applied Probability, 2023, vol. 25, issue 1, 1-21

Abstract: Abstract In this paper, we investigate the strong consistency for the conditional self-weighted M (SM, for short) estimator of generalized random coefficient autoregressive (GRCA(p), for short) model under some general assumptions. We obtain different estimators by taking different loss functions for the conditional SM estimation. What’s more, the simulation studies are provided by conducting three types of GRCA models. We allow that the variance of errors is finite or infinite, the numerical simulations are still valid. In addition, a real data example is given.

Keywords: Self-weighted M estimator; Generalized random coefficient autoregressive model; Strong consistency; Simulation; Real data analysis; 60F15; 62M10 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11009-022-09975-w

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