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 52
... defined on a complete metric space X has one and only one fixed point ; i.e. , the equation x has one and only one solution . Show that the generating function F ( s ) defined in [ 0,1 ] and satisfying the Lipschitz condition | F ( 82 ) ...
... defined on a complete metric space X has one and only one fixed point ; i.e. , the equation x has one and only one solution . Show that the generating function F ( s ) defined in [ 0,1 ] and satisfying the Lipschitz condition | F ( 82 ) ...
Page 211
... defined as the interval of time , following infection , during which the organisms are multiplying but the infected individual is unable to infect other individuals . The infectious period is defined as the interval of time during which ...
... defined as the interval of time , following infection , during which the organisms are multiplying but the infected individual is unable to infect other individuals . The infectious period is defined as the interval of time during which ...
Page 413
... defined as the ratio of the number of machines waiting to be serviced to the number of repairmen ; hence , b r = S ( m −1 , r , μ / 2 ) S ( m , r , μ / 2 ) which is one minus the coefficient of loss for repairmen . ( 9.130 ) For ...
... defined as the ratio of the number of machines waiting to be serviced to the number of repairmen ; hence , b r = S ( m −1 , r , μ / 2 ) S ( m , r , μ / 2 ) which is one minus the coefficient of loss for repairmen . ( 9.130 ) For ...
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 assume assumptions asymptotic birth process birth-and-death process boundary branching processes cascade process cascade theory coefficients collision consider counter defined denote the number denote the probability derive deterministic differential equation diffusion equations diffusion processes distribution function E₁ electron-photon cascades epidemic expression Feller finite fluctuation problem functional equation given Hence initial condition integral equation interval 0,t ionization Jánossy Kolmogorov equations Laplace transform Let the random machine Markov chain Markov processes Math mathematical matrix Mellin transform Messel method Monte Carlo methods neutron nucleon nucleon cascades number of individuals o(At obtain P₁ photon Phys Poisson process population probability distribution Proc queueing process queueing system r₁ r₂ radiation Ramakrishnan random variable random variable X(t recurrent satisfies Statist stochastic model Stochastic Processes t₁ t₂ Takács Theorem tion transition probabilities X₁ zero дх