Question

If $(X_t)$ is a Markov chain then $P(X_t=i|X_0=i)=\sum\limits_{k=1}^tP(X_1 \neq i, X_2\neq i,...,X_k=i,X_t=i|X_0=i)$

score 116 · Answer 1 · 2018-02-27 06:40:24

116

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If $(X_t)$ is a Markov chain then $P(X_t=i|X_0=i)=\sum\limits_{k=1}^tP(X_1 \neq i, X_2\neq i,...,X_k=i,X_t=i|X_0=i)$

Published on 27 Feb 2018 - 6:40

score 384 · Answer 2 · 2026-03-26 03:56:33

384

Views

Law of large numbers for Markov Chains

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48

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score 36 · Answer 4 · 2026-03-26 09:14:44

36

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153

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1.1k

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205

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336

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228

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325

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688

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List Question

If $(X_t)$ is a Markov chain then $P(X_t=i|X_0=i)=\sum\limits_{k=1}^tP(X_1 \neq i, X_2\neq i,...,X_k=i,X_t=i|X_0=i)$

Law of large numbers for Markov Chains

Stochastic Process: Is this a mistake or am I misunderstanding? (general two-state markov chain and finding $P(T\ge n)$

Difference between the joint probability $P(x_2,t_2;x_1,t_1)$ and the conditional probability $P(x_2,t_2|x_1,t_1)$

Is the sequence of return times a Markov Chain?

Stochastic Process: Shuffling a Card deck using random transpositions shuffle.

the average number of time period

physical intuition behind the probability transition of a probability matrix

Expected distance of the random walk at a random stopping time

Mean return time Markov Chain

Probability reaching recurrent states Markov chain

Stochastic Matrices Question

Stationary distribution for a Markov Chain on an uncountable space

"Distance" between distributions and convergence of Markov chains

transition rates from transition probabilities

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