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 8
... distribution F. Similar liberties will be taken for other terms . For example , convolution really signifies an operation , but the term is applied ... exponential distribution F do the tails 8 1.3 THE EXPONENTIAL AND THE UNIFORM DENSITIES.
... distribution F. Similar liberties will be taken for other terms . For example , convolution really signifies an operation , but the term is applied ... exponential distribution F do the tails 8 1.3 THE EXPONENTIAL AND THE UNIFORM DENSITIES.
Page 19
... exponential distributions , and this proves the proposi- tion . It follows ... distribution of X ( , ) and we have here another example of the advantage to ... exponential distribution . The service times of A and B commence immediately ...
... exponential distributions , and this proves the proposi- tion . It follows ... distribution of X ( , ) and we have here another example of the advantage to ... exponential distribution . The service times of A and B commence immediately ...
Page 39
... exponential , that is , h - 1 αe - ax for 0 < x < h for x > 0 . 5. Find the distribution functions of X + Y X and X + Y Ꮓ if the variables X , Y , and Z have a common exponential distribution . 6. If X and Y have the exponential ...
... exponential , that is , h - 1 αe - ax for 0 < x < h for x > 0 . 5. Find the distribution functions of X + Y X and X + Y Ꮓ if the variables X , Y , and Z have a common exponential distribution . 6. If X and Y have the exponential ...
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