## Elements of the theory of Markov processes and their applicationsGraduate-level text and reference in probability, with numerous scientific applications. Nonmeasure-theoretic introduction to theory of Markov processes and to mathematical models based on the theory. Appendixes. Bibliographies. 1960 edition. |

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Page 351

For a detailed discussion of radiative transfer theory we

Chandrasekar [3] and Kourganoff and Busbridge [6], and for a rigorous treatment

of the theory based on measure theory and functional analysis, we

work ...

For a detailed discussion of radiative transfer theory we

**refer**to the books ofChandrasekar [3] and Kourganoff and Busbridge [6], and for a rigorous treatment

of the theory based on measure theory and functional analysis, we

**refer**to thework ...

Page 372

For a stochastic approach to the kinetics of diffusion- controlled reactions we

to the paper of Waite [21]. And for some applications of the theory of diffusion-

controlled reactions to biological systems and the quenching of fluorescence we

...

For a stochastic approach to the kinetics of diffusion- controlled reactions we

**refer**to the paper of Waite [21]. And for some applications of the theory of diffusion-

controlled reactions to biological systems and the quenching of fluorescence we

...

Page 449

The method we

as the representation of a mathematical or physical system by a sampling

procedure which satisfies the same probability laws. Hence, the Monte Carlo

method ...

The method we

**refer**to is called the Monte Carlo method, and it can be describedas the representation of a mathematical or physical system by a sampling

procedure which satisfies the same probability laws. Hence, the Monte Carlo

method ...

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### Contents

Introduction | 1 |

Processes Discrete in Space and Time | 9 |

Processes Discrete in Space and Continuous in Time | 57 |

Copyright | |

10 other sections not shown

### Other editions - View all

Elements of the Theory of Markov Processes and Their Applications A. T. Bharucha-Reid Limited preview - 2012 |

Elements of the Theory of Markov Processes and Their Applications Albert T. Bharucha-Reid Limited preview - 1997 |

### Common terms and phrases

absorber Acad applications associated assume assumptions asymptotic birth process birth-and-death process branching processes cascade process cascade theory coefficient collision consider defined denote the number denote the probability derive determined deterministic differential equation diffusion equations diffusion processes distribution function electron-photon cascades epidemic exists expression Feller finite fluctuation problem functional equation given Hence initial condition integral equation interval ionization Kendall Kolmogorov equations Laplace transform Laplace-Stieltjes transform Let the random machine Markov chain Markov processes Math mathematical matrix mean and variance mean number Mellin transform Messel method Monte Carlo methods mutation neutron nonnegative nucleon nucleon cascades number of electrons number of individuals o(At obtain parameter photon Phys Poisson process probability distribution Proc Px(t queueing process queueing system radiation Ramakrishnan random variable random variable X(t reaction recurrent refer satisfies solution of Eq Statist stochastic model Stochastic Processes Theorem tion transition probabilities zero