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...Chapter discrete time markov chains in this we introduce for these models both and space are will begin by introducing the basic model provide some examples next construct a chain using only independent uniformly distributed random variables such construction demonstrate how to simulate which also be helpful continuous setting of later chapters finally develop theory let xn n beadiscretetimestochasticprocesswithadiscretestate s recallthats is said if it either nite or countably innite without loss generality nearly always assume that case understand behavior process would like know values p x i every sequence states note having dimensional distributions allows calculation any path probability example axioms j where second equality holds as events mutually exclusive c copyright david f anderson recall zk outcome kth roll fair die k then assuming rolls indpendent suppose frog can jump between three lily pads labeled on pad number with one similarly however when depict graphically via den...