What Is a Markov Chain? States, Matrices, Steady State

Overview

A Markov chain models a system that moves between states where the next state depends only on the current one. This documentation page explains the Markov property, the transition matrix (rows sum to 1), the classic Sunny/Rainy weather example computed step by step, the steady-state distribution, and absorbing states (the bridge to Markov cost-effectiveness models), then shows how SpiceLogic Rational Will and the Markov Chain Calculator build and run these models.

This is a draft. The full body (weather example with steady state pi = [5/6, 1/6] = [0.8333, 0.1667], verified) is generated and ready to expand here; the paired video plan is attached.