Nonparametric tests for transition probabilities in nonhomogeneous Markov processes.

ABSTRACT: This paper proposes nonparametric two-sample tests for the direct comparison of the probabilities of a particular transition between states of a continuous time non-homogeneous Markov process with a finite state space. The proposed tests are a linear nonparametric test, an L ²-norm-based test and a Kolmogorov-Smirnov-type test. Significance level assessment is based on rigorous procedures, which are justified through the use of modern empirical process theory. Moreover, the L ²-norm and the Kolmogorov-Smirnov-type tests are shown to be consistent for every fixed alternative hypothesis. The proposed tests are also extended to more complex situations such as cases with incompletely observed absorbing states and non-Markov processes. Simulation studies show

SUBMITTER: Bakoyannis G 

PROVIDER: S-EPMC7173284 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature