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open class DMarkovChain(theInitialState: Int = 1, transMatrix: Array<DoubleArray>, stream: RNStreamIfc = KSLRandom.nextRNStream()) : RVariable
Randomly generates the states of a discrete Markov Chain. Assumes that the states are labeled 1, 2, 3, etc. The transition probabilities are supplied as an array of arrays. transMatrix0 holds the array of transition probabilities for transition to each state {p11, p12, p13, .., p1n} for state 1 transMatrix1 holds the array of transition probabilities for transition to each state {p21, p22, p23, .., p2n} for state 2 etc.
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class TwoStateMarkovChain(theInitialState: Int = 1, val p01: Double = 0.5, val p11: Double = 0.5, stream: RNStreamIfc = KSLRandom.nextRNStream()) : RVariable