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hal-00704611, version 1

On the quasi-likelihood estimation for random coefficient autoregressions

Lionel Truquet () 1, Jian-Feng Yao 2

Statistics 46, 4 (2012) 505-521

Abstract: We examine the Gaussian quasi-maximum likelihood estimator (QMLE) for random coefficient autoregressions. Consistency and asymptotic normality are established for general random coefficients and general correlation structure between these coefficients and the noise. In particular, the obtained results apply even if the stationary solution has infinite absolute mean or infinite variance. Next an application to the integer-valued times series modelling is given which provides a novel alternative for traditional INAR-like models for these series.

  • 1:  Institut de Recherche Mathématique de Rennes (IRMAR)
  • CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
  • 2:  Department of Statistics and Actuarial Science [University of Hong Kong] (DSAS)
  • University of Hong Kong
  • Domain : Mathematics/Statistics
    Statistics/Statistics Theory
  • Keywords : quasi-likelihood estimation – random coefficient autoregressions – integer-valued time series
 
  • hal-00704611, version 1
  • http://hal.archives-ouvertes.fr/hal-00704611
  • oai:hal.archives-ouvertes.fr:hal-00704611
  • From: Marie-Annick Guillemer <>
  • Submitted on: Tuesday, 5 June 2012 17:35:39
  • Updated on: Monday, 10 December 2012 17:13:37