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Discrete Random Variables: Basics
"... • Given an experiment and the corresponding set of possible outcomes (the sample space), a random variable associates a particular number with each ..."
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• Given an experiment and the corresponding set of possible outcomes (the sample space), a random variable associates a particular number with each
Discrete Random Variables Over Domains
"... Abstract. In this paper we explore discrete random variables over domains. We show that these lead to a continuous endofunctor on the categories RB (domains that are retracts of bifinite domains), and FS (domains where the identity map is the directed supremum of deflations finitely separated from t ..."
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Cited by 3 (0 self)
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Abstract. In this paper we explore discrete random variables over domains. We show that these lead to a continuous endofunctor on the categories RB (domains that are retracts of bifinite domains), and FS (domains where the identity map is the directed supremum of deflations finitely separated from
Optimal Algorithms for Generating Discrete Random Variables With . . .
 IN PROCEEDINGS20 TH INTERNATIONAL COLLOQUIUM ON AUTOMATA, LANGUAGESAND PROGRAMMING,VOLUME 700 OF LECTURE NOTES IN COMPUTER SCIENCE
, 1992
"... We give optimal algorithms for generating discrete random variables for changing distributions. We discuss two models of how distributions may change. In both models, we obtain a solution with constant update time, constant expected generate time, and linear space. ..."
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Cited by 7 (2 self)
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We give optimal algorithms for generating discrete random variables for changing distributions. We discuss two models of how distributions may change. In both models, we obtain a solution with constant update time, constant expected generate time, and linear space.
Geometric constructions with discretized random variables
 RELIABLE COMPUTING
, 2006
"... We generalize the DEnv (Distribution envelope determination) method for bounding the result of arithmetic operations on random variables with unknown dependence to higherdimensional settings. In order to minimize both the influence of the coordinate frame and information loss we suggest a nested ..."
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Cited by 2 (0 self)
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We generalize the DEnv (Distribution envelope determination) method for bounding the result of arithmetic operations on random variables with unknown dependence to higherdimensional settings. In order to minimize both the influence of the coordinate frame and information loss we suggest a nested
Algorithms for Computing the Distributions of Sums of Discrete Random Variables
, 2003
"... Abstract—We present algorithms for computing the probablity density function of the sum of two independent discrete random variables, along with an implementation of the algorithm in a computer algebra system. Some examples illustrate the utility of this algorithm. c ○ 2004 Elsevier Science Ltd. All ..."
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Abstract—We present algorithms for computing the probablity density function of the sum of two independent discrete random variables, along with an implementation of the algorithm in a computer algebra system. Some examples illustrate the utility of this algorithm. c ○ 2004 Elsevier Science Ltd
Discrete Random Variables: Basics Reference:
"... • Given an experiment and the corresponding set of possible outcomes (the sample space), a random ..."
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• Given an experiment and the corresponding set of possible outcomes (the sample space), a random
Extremal Limit Laws for Discrete Random Variables
"... If X1,X2,...,Xn are independent and identically distributed discrete random variables and Mn = max(X1,...,Xn) we examine the limiting behavior of (Mn − b(n))/a(n) as n→∞. It is well known that for discrete distributions such as Poisson and geometric the limiting distribution is not nondegenerate. H ..."
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If X1,X2,...,Xn are independent and identically distributed discrete random variables and Mn = max(X1,...,Xn) we examine the limiting behavior of (Mn − b(n))/a(n) as n→∞. It is well known that for discrete distributions such as Poisson and geometric the limiting distribution is not non
Uniformly Generating Distribution Functions for Discrete Random Variables
, 2000
"... An algorithm is presented which, with optimal efficiency, solves the problem of uniform random generation of distribution functions for an nvalued random variable. 1 ..."
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An algorithm is presented which, with optimal efficiency, solves the problem of uniform random generation of distribution functions for an nvalued random variable. 1
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