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Markov Chains Compact Lecture Notes and Exercises

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Markov ChainsCompact Lecture Notes and ExercisesSeptember 2009ACC CoolenDepartment of MathematicsKing s College London~ @@@R@@@R@@@R @@@R @@@R part of course 6CCM320Apart of course 6CCM380A21 Introduction32 Definitions and properties of stochastic Stochastic processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Markov Chains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Properties of homogeneous finite state space Markov Simplification of notation & formal solution.

Markov chains are discrete state space processes that have the Markov property. Usually they are deflned to have also discrete time (but deflnitions vary slightly in textbooks).

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