State Aggregations in Markov Chains and Block Models of Networks

Empirical Bayes Estimation in Nonstationary Markov chains

Estimation procedures for nonstationary Markov chains appear to be relatively sparse. This work introduces empirical  Bayes estimators  for the transition probability  matrix of a finite nonstationary  Markov chain. The data are assumed to be of  a panel study type in which each data set consists of a sequence of observations on N>=2 independent and identically dis...

Regenerative block empirical likelihood for Markov chains

Approximate regenerative-block bootstrap for Markov chains

Markov chains on orthogonal block structures

In this paper we define a particular Markov chain on some combinatorial structures called orthogonal block structures. These structures include, as a particular case, the poset block structures, which can be naturally regarded as the set on which the generalized wreath product of permutation groups acts as the group of automorphisms. In this case, we study the associated Gelfand pairs together ...

Modeling haplotype block variation using Markov chains.

Models of background variation in genomic regions form the basis of linkage disequilibrium mapping methods. In this work we analyze a background model that groups SNPs into haplotype blocks and represents the dependencies between blocks by a Markov chain. We develop an error measure to compare the performance of this model against the common model that assumes that blocks are independent. By ex...