What is the difference between all types of Markov Chains?
Apr 25, 2017 · A Markov process is basically a stochastic process in which the past history of the process is irrelevant if you know the current system state. In other words, all information about …
Markov Chain - Absorption - Mathematics Stack Exchange
Apr 12, 2021 · I am interested in learning about Markov chains, for that I am doing the following exercise and I am generating the following questions: I have the following matrix of one-step …
Markov chain having unique stationary distribution
Jan 24, 2023 · In general, stationary distributions for finite Markov chains exist if and only if the chain is irreducible, in which case the stationary distribution is unique if and only if the chain is …
property about transient and recurrent states of a Markov chain
Dec 25, 2020 · All states of a finite irreducible Markov chain are recurrent. As irreducible Markov chains have one class, statement $1$ implies all states are either transient or recurrent.
what is the difference between a markov chain and a random walk?
Jun 17, 2022 · I think Surb means any Markov Chain is a random walk with Markov property and an initial distribution. By "converse" he probably means given any random walk , you cannot …
probability - How to prove that a Markov chain is transient ...
Oct 5, 2023 · probability probability-theory solution-verification markov-chains random-walk See similar questions with these tags.
reference request - What are some modern books on Markov …
I would like to know what books people currently like in Markov Chains (with syllabus comprising discrete MC, stationary distributions, etc.), that contain many good exercises. Some such book …
Book on Markov Decision Processes with many worked examples
I am looking for a book (or online article (s)) on Markov decision processes that contains lots of worked examples or problems with solutions. The purpose of the book is to grind my teeth on …
How to characterize recurrent and transient states of Markov chain
6 Tim's characterization of states in terms of closed sets is correct for finite state space Markov chains. Partition the state space into communicating classes. Every recurrent class is closed, …
probability - Understanding the "Strength" of the Markov Property ...
Jan 13, 2024 · The strong markov property is an altogether different animal because it requires deep understanding of what a continuous time markov chain is. Yes, brownian motion is a ct …