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...

Jun 6, 2025 · In a Markov process, a null recurrent state is returned to, but just not often enough for the return to be classified as periodic with any finite period. (eg. returning, on average once every 4.5 …

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.

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 …

Markov processes and, consequently, Markov chains are both examples of stochastic processes. Random process and stochastic process are completely interchangeable (at least in many books on …

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

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 …

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

Now in markov chain a steady state vector ( when effect multiplying or any kind of linear transformation on prob state matrix yield same vector) : qp=q where p is prob state transition matrix this means Y = …

15 Markov's inequality is a "large deviation bound". It states that the probability that a non-negative random variable gets values much larger than its expectation is small. Chebyshev's inequality is a …