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 the …
'Snakes and Ladders' As a Markov Chain? - Mathematics Stack Exchange
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 …
Properties of Markov chains - Mathematics Stack Exchange
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...
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 mc but that's …
Relationship between Eigenvalues and Markov Chains
Jan 22, 2024 · I am trying to understand the relationship between Eigenvalues (Linear Algebra) and Markov Chains (Probability). Particularly, these two concepts (i.e. Eigenvalues and Markov Chains) …
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 aperiodic (this …
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 conclude …
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.
Why Markov matrices always have 1 as an eigenvalue
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 = …