2015/01/22 by Tomasz R. Bielecki, Bielecki, Tomasz R., Jacek Jakubowski +3
Computer Science · Mathematics · #60G55 #60J27 #Bayesian Modeling and Causal Inference #FOS: Mathematics #Probability (math.PR) #Statistical Methods and Inference #Statistical Methods in Clinical Trials #math.PR #msc:60G55 #msc:60J27
paper · pdf · doi:10.48550/arxiv.1501.05531
openalex publication_date 2015/01/22 · arxiv created 2015/11/30 · arxiv updated 2015/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we continue the study of conditional Markov chains (CMCs) with finite state spaces, that we initiated in Bielecki, Jakubowski and Niewęgłowski (2014a) in an effort to enrich the theory of CMCs that was originated in Bielecki and Rutkowski (2004). We provide an alternative definition of a CMC and an alternative construction of a CMC via a change of probability measure. It turns out that our construction produces CMCs that are also doubly stochastic Markov chains (DSMCs), which allows for study of several properties of CMCs using tools available for DSMCs.