We covered Markov chains in class and after going through the details, I still have a few questions. (I encourage you to give short answers to the question, as this may become very cumbersome other...

Jan 25, 2023 · Continuous Time Markov Chain: Characterized by a time dependent transition probability matrix "P (t)" and a constant infinitesimal generator matrix "Q". The Continuous Time Markov Chain …

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 the …

Dec 25, 2020 · All states of a finite irreducible Markov chain are recurrent. As irreducible Markov chains have one class, statement 1 1 implies all states are either transient or recurrent.

Oct 5, 2023 · probability probability-theory solution-verification markov-chains random-walk See similar questions with these tags.

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 some …

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, but no …

Mar 11, 2015 · Markov's Inequality and its corollary Chebyshev's Inequality are extremely important in a wide variety of theoretical proofs, especially limit theorems. A previous answer provides an example.

May 18, 2015 · Transition probabilities of Markov Chains most definitely can depend on time. The ones that don't are called time-homogeneous. For instance in a discrete time discrete state Markov Chain, …

Aug 14, 2016 · My question is a bit more basic, can the difference between the strong Markov property and the ordinary Markov property be intuited by saying: "the Markov property implies that a Markov …