Elements of Applied Stochastic ProcessesJ. Wiley, 1972 - 414 páginas Stochastic processes: description and definition; The two-state markov process; Markov chains: classification of states; Finite markov chains; Markov chains with countably infinite states; Simple markov processes; Renewal processes; Stationary processes: some general properties; Markov decision processes; Congestion processes; Stochastic processes in reliability theory; Time series analysis; Social and behavioral processes; Some markov models in business and sports. |
Contenido
INTRODUCTION | 1 |
2 | 11 |
THE TWOSTATE MARKOV PROCESS | 18 |
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analysis Applications arrival assume assumptions behavior birth and death called Chapter Clearly component consider continuous cost customers death process defined DEFINITION dependent derived determine discrete discussed elements equations estimates Example exists expected finite function Further given gives hence independent initial interested interval known length likelihood limiting distribution Markov chain Markov process mean method negative exponential noted number of customers o(At observed obtained operation parameter period points Poisson process population positive possible problems Proof properties queue random variables recurrent referred renewal replacement representing respectively sample server similar simple situations solution space started stationary statistic steps stochastic process Suppose Theorem Theory transient transition probability matrix trials unit variance vector waiting write York zero