Some results on the estimation of a higher order Markov chain

Wai Keung LI, Michael C.O. KWOK

Research output: Contribution to journalArticles

8 Citations (Scopus)

Abstract

Raftery (1985) proposed a higher order Markov model that is parsimonious in terms of number of parameters. The model appears to be useful in many real life situations. However, many important properties of the model have not been investigated. In particular, estimation methods under various sampling situations have not been studied. In this paper the relative merits of the maximum likelihood and the minimum chi-square estimators for a single realization are considered. For other sampling situations, a nonlinear least squares estimator is proposed when only macro data are available. Its small sample properties are studied by simulation. An empirical Bayes estimator for panel data is also considered. Copyright © 1990 Taylor & Francis Group, LLC. All rights reserved.
Original languageEnglish
Pages (from-to)363-380
JournalCommunications in Statistics - Simulation and Computation
Volume19
Issue number1
DOIs
Publication statusPublished - 1990

Citation

Li, W. K., & Kwok, M. C. O. (1990). Some results on the estimation of a higher order Markov chain. Communications in Statistics - Simulation and Computation, 19(1), 363-380. doi: 10.1080/03610919008812862

Keywords

  • Empirical Bayes estimator
  • Higher order Markov chain
  • Macro data
  • Maximum likelihood estimator
  • Minimum chi-square estimator

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