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The Kendall theorem and its application to the geometric ergodicity of Markov chains

Witold Bednorz (2013)

Applicationes Mathematicae

We give an improved quantitative version of the Kendall theorem. The Kendall theorem states that under mild conditions imposed on a probability distribution on the positive integers (i.e. a probability sequence) one can prove convergence of its renewal sequence. Due to the well-known property (the first entrance last exit decomposition) such results are of interest in the stability theory of time-homogeneous Markov chains. In particular this approach may be used to measure rates of convergence of...

The multisample version of the Lepage test

František Rublík (2005)

Kybernetika

The two-sample Lepage test, devised for testing equality of the location and scale parameters against the alternative that at least for one of the parameters the equality does not hold, is extended to the general case of k > 1 sampled populations. It is shown that its limiting distribution is the chi-square distribution with 2 ( k - 1 ) degrees of freedom. This k -sample statistic is shown to yield consistent test and a formula for its noncentrality parameter under Pitman alternatives is derived. For some particular...

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