Markov Chain Order Estimation and Relative Entropy

We use the f − divergence also called relative entropy as a measure of diversity between probability densities and review the basic properties of the estimator D 2 (..). In the sequence we define a few objects which capture relevant information from the sample of a Markov Chain to be used in the definition of a couple of estimators i.e. the Local Dependency Level and Global Dependency Level for a Makov chain sample. After exploring their properties we propose a new estimator for the Markov chain order. Finally we show a few tables containing numerical simulation results, comparing the performance of the new estimator with the well known and already established AIC and BIC estimators.