An Introduction to Probability Theory and Its Applications, Volume 2Wiley, 1950 - Probabilities Vol. 2 has series: Wiley series in probability and mathematical statistics. Bibliographical footnotes. "Some books on cagnate subjects": v. 2, p. 615-616. |
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Page 179
... example a discontinuity is guaranteed at t = 1 , 2 , . . . . Examples for empirical applications . An unending variety of practical problems can be reduced to compound Poisson processes . Here are a few typical examples . ( i ) The ...
... example a discontinuity is guaranteed at t = 1 , 2 , . . . . Examples for empirical applications . An unending variety of practical problems can be reduced to compound Poisson processes . Here are a few typical examples . ( i ) The ...
Page 392
... example of the economy of thought inherent in a general theory where one's view is not obscured by accidents of ... example XVIII , ( 3c ) . ( b ) The dual case . Consider the same distributions as in the last example but with μ < 0 . As ...
... example of the economy of thought inherent in a general theory where one's view is not obscured by accidents of ... example XVIII , ( 3c ) . ( b ) The dual case . Consider the same distributions as in the last example but with μ < 0 . As ...
Page 558
... example ( b ) was discovered in special cases by Gnedenko , Khintchine , and Lévy . It is interesting to observe the complications encountered in a special example when the underlying phenomenon of regular variation is not properly ...
... example ( b ) was discovered in special cases by Gnedenko , Khintchine , and Lévy . It is interesting to observe the complications encountered in a special example when the underlying phenomenon of regular variation is not properly ...
Contents
CHAPTER | 1 |
SPECIAL DENSITIES RANDOMIZATION | 44 |
PROBABILITY MEASURES AND SPACES | 101 |
Copyright | |
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An Introduction to Probability Theory and Its Applications, Volume 2 William Feller Limited preview - 1991 |
Common terms and phrases
a₁ applies arbitrary argument assume asymptotic atoms backward equation Baire functions Borel sets bounded central limit theorem characteristic function common distribution compound Poisson condition consider constant continuous function convergence convolution defined definition denote density derived distribution F distribution function equals example exists exponential distribution F{dx finite interval fixed follows formula given hence implies independent random variables inequality infinitely divisible integral integrand Laplace transform law of large left side lemma Let F limit distribution Markov martingale measure mutually independent normal distribution notation o-algebra obvious operator parameter Poisson process positive probabilistic probability distribution problem proof prove random walk renewal epochs renewal equation renewal process S₁ sample space satisfies semi-group sequence shows solution stable distributions stochastic stochastic kernel symmetric T₁ tends theory transition probabilities uniformly unique variance vector X₁ Y₁ zero expectation