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 …

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 …

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 …

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 …

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.

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

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 …

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 …

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, …

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 …