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 2
... sample space and to assign to each interval its length as probability . The conceptual experiment of making two independent random choices of points in 0 , 1 results in a pair of real numbers , and so the natural sample space is a unit ...
... sample space and to assign to each interval its length as probability . The conceptual experiment of making two independent random choices of points in 0 , 1 results in a pair of real numbers , and so the natural sample space is a unit ...
Page 2
... sample space and to assign to each interval its length as probability . The conceptual experiment of making two independent random choices of points in 0 , 1 results in a pair of real numbers , and so the natural sample space is a unit ...
... sample space and to assign to each interval its length as probability . The conceptual experiment of making two independent random choices of points in 0 , 1 results in a pair of real numbers , and so the natural sample space is a unit ...
Page 13
... sample space has these step functions as sample points ; the sample space is a function space - the space of all conceivable “ paths . " In this space N ( t ) is defined as the value of the ordinate at epoch t and S , as the coordinate ...
... sample space has these step functions as sample points ; the sample space is a function space - the space of all conceivable “ paths . " In this space N ( t ) is defined as the value of the ordinate at epoch t and S , as the coordinate ...
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