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 …

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...

Oct 3, 2022 · If this was the original game of Snakes and Ladders with only one die, I have seen many examples online that show you how to model this game using a Markov Chain and how to create the …

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 conclude …

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

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.

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 on

Note that this version of the Riesz-Markov-Kakutani theorem is much stronger than the usually stated one, which is concerned positive functionals on $\mathbb {R}$. The fact that the dual norm is the …

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 …

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 mc but that's …