The estimation of random coefficient autoregressive models. I

D. F. Nicholls*, B. G. Quinn

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)

Abstract

Abstract. This paper is concerned with autoregressive models in which the coefficients are assumed to be not constant but subject to random perturbations so that we are considering a class of random coefficient autoregressive models. By means of a two stage regression procedure estimates of the unknown parameters of these models are obtained. The estimates are shown to be strongly consistent and to satisfy a central limit theorem. A number of Monte Carlo experiments was carried out to illustrate the estimation procedure and their results are reported.

Original languageEnglish
Pages (from-to)37-46
Number of pages10
JournalJournal of Time Series Analysis
Volume1
Issue number1
DOIs
Publication statusPublished - 1980
Externally publishedYes

Keywords

  • central limit theorem
  • Monte Carlo experiment
  • random coefficient autoregression
  • strong consistency

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