Markov Chains (2D) — State Diagram & Stationary Distribution

⚙️ Controls

Preset State count (random preset) 4 Step delay 600 ms

Current state

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Step #

Most visited

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Convergence

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ℹ️ About

A Markov chain is a stochastic process where each transition depends only on the current state. The stationary distribution π satisfies π = πP and is found here by power iteration. Bars compare empirical (observed) vs theoretical (π) visit frequencies.