MKVPCI: a computer program for Markov models with piecewise constant intensities and covariates
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Updated: Oct 10, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
1ISPED and INSERM U330, Université Victor Segalen, Bordeaux 2, 146, rue Léo-Saignat, 33076 Cedex, Bordeaux, France. alioum.ahmadou@dim.u-bordequx2.fr
Abstract:
We present a computer program for fitting Markov models with piecewise constant intensities and for estimating the effect of covariates on transition intensities. The basic idea of the proposed approach is to introduce artificial time-dependent covariates in the data to represent the time dependence of the transition intensities, and to use a modified time-homogeneous Markov model to estimate the baseline transition intensities and the regression coefficients. The program provides the maximum likelihood estimates of the parameters together with their estimated standard errors, and allows testing various statistical hypotheses. To illustrate the use of the program, we present a three-state model for analyzing the smoking habits of school children.
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