Results 221 to 230 of about 6,151,667 (279)

The Hypergeometric Distribution as a More Accurate Model for Stochastic Computing

Design, Automation and Test in Europe, 2020
A fundamental assumption in stochastic computing (SC) is that bit-streams are generally well-approximated by a Bernoulli process, i.e., a sequence of independent 0-1 choices.
T. Baker, J. Hayes
semanticscholar   +1 more source

A Conway Maxwell Poisson type generalization of the negative hypergeometric distribution

Communications in Statistics - Theory and Methods, 2020
Negative hypergeometric distribution arises as a waiting time distribution when we sample without replacement from a finite population. It has applications in many areas such as inspection sampling and estimation of wildlife populations.
Sudip Roy, R. Tripathi, N. Balakrishnan
semanticscholar   +1 more source

A Hypergeometric Distribution [PDF]

, 1989
There are many instances wherein you use samples to help you make decisions, though not in the formal ways we shall be developing in this course. For example, the authors examine a box of strawberries in the supermarket and, seeing at most one or two berries with “spots”, buy the box. The other way around, a nut broker examines a handful of nuts from a
Hung T. Nguyen, Gerald S. Rogers
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Tables of the Hypergeometric Probability Distribution.

Mathematics of Computation, 1961
Gerald J. Lieberman and Donald B. Owen: Tables of the Hypergeometric Probability Distribution. California: Stanford University Press; London: Oxford University Press, 1961. Pp. vi + 726. ®6.
R. A. Bradley, Gerald J. Lieberman, Donald B. Owen   +2 more
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On the negative hypergeometric distribution

International Journal of Mathematical Education in Science and Technology, 1987
A negative hypergeometric random variable, Yr, records the waiting time in trials until the rth success is obtained in repeated random sampling without replacement from a dichotomous population of N containing n ( ≥ r) successes S, and m failures F. In this paper we give a probability space for Yr and a representation of Yr in terms of exchangeable ...
William R. Sype, Eugene F. Schuster
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Concentration of the hypergeometric distribution

Statistics & Probability Letters, 2005
In this paper we provide an improved concentration of measure theorem for the hypergeometric distribution.
Clint Scovel, Don Hush
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The redundant hypergeometric distribution

International Journal of Mathematical Education in Science and Technology, 1987
The redundant hypergeometric distribution results from a model similar to that for the ordinary hypergeometric, but where selections are made ‘redundantly’. The distribution has applications in the area of statistical physics. However, the probability function is elementary and standard properties may be derived by familiar techniques.
J. A. Shanks, John C. W. Rayner
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An approximation to the generalized hypergeometric distribution [PDF]

Statistical Papers, 2003
A generalized hypergeometric (GHG) distribution was defined, and its higher order approximations were given by Takeuchi (1984). In this paper, an improvement on the approximation is considered and examined by the numerical calculation. Several examples including the Poisson, binomial, negative-binomial, hypergeometric and negative-hypergeometric ...
Eisuke Hida, Masafumi Akahira
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A Characterization of Hypergeometric Distributions

Journal of the American Statistical Association, 1970
Abstract A theorem, that mixtures with binomial mixing distribution which are themselves binomial characterize the hypergeometric family of distributions, is displayed in various forms (the theorem and three equivalent restatements). These exhibit the fact that the property in question is related in a fundamental way to properties of moment sequences ...
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On Characterizing the Hypergeometric and Multivariate Hypergeometric Distributions

1975
Skibinsky characterized the classical univariate hypergeometric distribution in terms of the reproducibility of the binomial distribution with respect to sampling without replacement.
A. M. Nevill, C. D. Kemp
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