Variable Length Markov Chains, Persistent Random Walks: a close encounter

Peggy Cénac (1) , Brigitte Chauvin (2) , F. Paccaut (3) , Nicolas Pouyanne (2)

1 IMB - Institut de Mathématiques de Bourgogne [Dijon]
2 LMV - Laboratoire de Mathématiques de Versailles
3 LAMFA - Laboratoire Amiénois de Mathématique Fondamentale et Appliquée - UMR CNRS 7352

This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov, autoregressive and piecewise deterministic Markov models. The material is divided into three parts corresponding to: (i) Markov and semi-Markov processes, (ii) autoregressive processes and (iii) techniques based on divergence measures and entropies. A special attention is payed to applications in reliability, survival analysis and related fields.

Domaines: Probabilités [math.PR]

Peggy Cénac, Brigitte Chauvin, F. Paccaut, Nicolas Pouyanne. Variable Length Markov Chains, Persistent Random Walks: a close encounter. Statistical Topics and Stochastic Models for Dependent Data with Applications, Wiley-ISTE, pp.3-27, 2020, Mathematics and Statistics, 978-1-786-30603-6. ⟨hal-03555213⟩