Regenerative block empirical likelihood for Markov chains

Regenerative block empirical likelihood for Markov chains

Approximate regenerative-block bootstrap for Markov chains

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...

Quasi-likelihood regression models for Markov chains

We consider regression models in which covariates and responses jointly form a higher order Markov chain. A quasi-likelihood model speciies parametric models for the conditional means and variances of the responses given the past observations. A simple estimator for the parameter is the maximum quasi-likelihood estimator. We show that it does not use the information in the model for the conditi...

Note: Maximum Likelihood Estimation for Markov Chains

1 Derivation of the MLE for Markov chains To recap, the basic case we’re considering is that of a Markov chain X∞ 1 with m states. The transition matrix, p, is unknown, and we impose no restrictions on it, but rather want to estimate it from data. The parameters we wish to infer are thus them matrix entries pij , which are defined as pij = Pr (Xt+1 = j|Xt = i) (1) What we observe is a sample fr...