Approximating Countable Markov Chains |
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... independent and exponential , with common param- eter q ( k ) . There are two kinds of cuts : the first kind appears at a jump of X ,, and the second kind appears interior to an interval of constancy for Xj . Cuts of the first kind ...
... independent and exponential , with common param- eter q ( k ) . There are two kinds of cuts : the first kind appears at a jump of X ,, and the second kind appears interior to an interval of constancy for Xj . Cuts of the first kind ...
Page 2
... independent and exponential , with common param- eter qÅ ( k ) . There are two kinds of cuts : the first kind appears at a jump of X ,, and the second kind appears interior to an interval of constancy for Xj . Cuts of the first kind ...
... independent and exponential , with common param- eter qÅ ( k ) . There are two kinds of cuts : the first kind appears at a jump of X ,, and the second kind appears interior to an interval of constancy for Xj . Cuts of the first kind ...
Page 31
... independent and exponential with parameter q . If is Poisson with parameter q , then ( MC , 5.39 ) shows that ( 69a ) P And an easy integration shows that ( 69b ) X has stationary , independent increments . Prob { X ( t ) = = n } ( qt ) ...
... independent and exponential with parameter q . If is Poisson with parameter q , then ( MC , 5.39 ) shows that ( 69a ) P And an easy integration shows that ( 69b ) X has stationary , independent increments . Prob { X ( t ) = = n } ( qt ) ...
Contents
RESTRICTING THE RANGE | 1 |
RESTRICTING THE RANGE APPLICATIONS | 64 |
CONSTRUCTING THE GENERAL MARKOV CHAIN | 95 |
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1)-intervals a₁ absorbing argue argument b₂ binary rationals Brownian Motion chapter coincides conditional distribution construction converges David Freedman defined exponentially distributed F(1)-measurable Figure finite subset Fubini hitting holding i₁ implies In+1 independent and exponential infinite interval of constancy j₁ joint distribution jump Lebesgue measure Lemma Let f locally finitary Markov chain Markov process Markov property Markov with stationary Markov with transitions Math nondecreasing notation null set P-distribution P-probability P₁ Poisson process Poisson with parameter positive Prob probability triple product measurable prove pseudo-jumps Qn(i QN(j Qn+1 quasiregular random variables recurrent restriction retracted right continuous sample functions satisfies Section sequence spends interior standard stochastic semigroup starting stationary standard transitions stationary transitions strictly increasing Suppose T₁ Theorem TJ,n TJ,o TN,o visits VOLKER STRASSEN WILLIAM FELLER X₁ XN+1 YN+m