Tests for semiparametric model based on non-homogeneous Markov process

Leszek Marzec and Pawel Marzec

Statistics & Probability Letters, 1996, vol. 27, issue 2, 137-143

Abstract: In the paper the semiparametric Markov process model is considered. This model describes the effect of an observable covariate process on the transition intensity. A multivariate process based on the observed jumps between the states of Markov process is defined. Its weak convergence to a continuous Gaussian martingale is established which leads to the formal construction of the Cramer-von Mises, Kolmogorov-Smirnov and [chi]2-type goodness-of-fit tests. The optimality problem in the class of tests under a sequence of local alternatives is also discussed.

Keywords: Goodness-of-fit; Counting; process; Markov; process; Cox; regression; model; Martingale; Weak; convergence (search for similar items in EconPapers)
Date: 1996
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Citations: View citations in EconPapers (1)

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