Discrete-time Markov chain: Difference between revisions

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As ''n'' was arbitrary, this reasoning holds for any ''n'', and therefore for reversible Markov chains '''{{pi}}''' is always a steady-state distribution of Pr(''X''<sub>''n''+1</sub>&nbsp;=&nbsp;''j''&nbsp;|&nbsp;''X''<sub>''n''</sub>&nbsp;=&nbsp;''i'') for every&nbsp;''n''.
 
If the Markov chain begins in the steady-state distribution, that is, if <math>\Pr(X_0=i)=\pi_i</math>, then <math>\Pr(X_n=i)=\pi_i</math> for all <math>n</math> and the detailed balance equation can be written as
 
:<math>\Pr(X_{n} = i, X_{n+1} = j) = \Pr(X_{n+1} = i, X_{n} = j)\,.</math>