Comptes Rendus
Statistics/Probability Theory
Goodness-of-fit test for homogeneous Markov processes
Comptes Rendus. Mathématique, Volume 351 (2013) no. 3-4, pp. 149-154.

We give chi-squared goodness-of-fit tests for homogeneous Markov processes with unknown transition intensities or with transition intensities of known form depending on a finite-dimensional parameter.

On propose des tests dʼajustement du type chi deux de lʼhypothèse selon laquelle un processus stochastique dʼespace dʼétats fini est un processus de Markov homogène, dont les intensités de transition sont, ou inconnues, ou des fonctions spécifiées dʼun paramètre de dimension finie.

Received:
Accepted:
Published online:
DOI: 10.1016/j.crma.2013.01.014
Vilijandas Bagdonavičius 1; Mikhail Nikulin 2

1 University of Vilnius, 24, Naugarduko, Vilnius, Lithuania
2 Université Victor-Segalen, Bordeaux-1, 351, cours de la Libération, 33405 Talence cedex, France
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Vilijandas Bagdonavičius; Mikhail Nikulin. Goodness-of-fit test for homogeneous Markov processes. Comptes Rendus. Mathématique, Volume 351 (2013) no. 3-4, pp. 149-154. doi : 10.1016/j.crma.2013.01.014. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2013.01.014/

[1] R. Aguirre-Hernandez; V.T. Farewell A Pearson-type goodness-of-fit test for stationary and time-continuous Markov regression models, Stat. Med., Volume 21 (2002), pp. 1899-1911

[2] M.G. Akritas Pearson-type goodness-of-fit tests: the univariate case, J. Am. Stat. Assoc., Volume 83 (1988), pp. 222-230

[3] P.K. Andersen; O. Borgan; R.D. Gill; N. Keiding Statistical Models Based on Counting Processes, Springer-Verlag, New York, 1993

[4] V. Bagdonavičius; M. Nikulin Chi-squared goodness-of-fit test for right censored data, Int. J. Appl. Math. Stat., Volume 24 (2011), pp. 30-50

[5] N.L. Hjort Goodness of fit tests in models for life history data based on cumulative hazard rates, Ann. Stat., Volume 18 (1990), pp. 1221-1258

[6] J.D. Kalbfleisch; J.F. Lawless The analysis of panel data under a Markov assumption, J. Am. Stat. Assoc., Volume 80 (1985), pp. 863-871

[7] A. Rindos; S. Woolet; I. Viniotis; K. Trivedi Exact methods for the transient analysis of nonhomogeneous continuous time Markov chains (W.J. Stewart, ed.), Computations with Markov Chains, Kluwer Academic Publishers, Boston, 1995, pp. 121-133 (Chapter 8)

[8] A.C. Titman; L.D. Sharples A general goodness-of-fit test for Markov and hidden Markov models, Stat. Med., Volume 27 (2008), pp. 2177-2195

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