Csc2420: Algorithm Design, Analysis and Theory Topic: Markov Chain and Randomized Rounding 22.1 Outline 22.2 Markov Chain 22.2.1 the Basics
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چکیده
A state i is said to be transient if fii < 1; and it is said to be persistent if fii = 1. Denote by q = (q 1, q t 2, . . . , q t n) the state probability vector (the distribution of the chain at time t), to be a row vector whose i-th component is the probability that the Markov chain is in state i at time t. A distribution π is a stationary distribution for a Markov chain with transition matrix P if π = πP .
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