词条 | Van Houtum distribution |
释义 |
}}{{Probability distribution| name =Van Houtum distribution| type =mass| pdf_image =| parameters =| support =| pdf =| cdf =| median = | mean =| variance = | mode =N/A| skewness = | kurtosis = | entropy = | mgf = | cf = | }} In probability theory and statistics, the Van Houtum distribution is a discrete probability distribution named after prof. Geert-Jan van Houtum.[1] It can be characterized by saying that all values of a finite set of possible values are equally probable, except for the smallest and largest element of this set. Since the Van Houtum distribution is a generalization of the discrete uniform distribution, i.e. it is uniform except possibly at its boundaries, it is sometimes also referred to as quasi-uniform. It is regularly the case that the only available information concerning some discrete random variable are its first two moments. The Van Houtum distribution can be used to fit a distribution with finite support on these moments. A simple example of the Van Houtum distribution arises when throwing a loaded dice which has been tampered with to land on a 6 twice as often as on a 1. The possible values of the sample space are 1, 2, 3, 4, 5 and 6. Each time the die is thrown, the probability of throwing a 2, 3, 4 or 5 is 1/6; the probability of a 1 is 1/9 and the probability of throwing a 6 is 2/9. Probability mass functionA random variable U has a Van Houtum (a, b, pa, pb) distribution if its probability mass function is Fitting procedureSuppose a random variable has mean and squared coefficient of variation . Let be a Van Houtum distributed random variable. Then the first two moments of match the first two moments of if , , and are chosen such that:[2] There does not exist a Van Houtum distribution for every combination of and . By using the fact that for any real mean the discrete distribution on the integers that has minimal variance is concentrated on the integers and , it is easy to verify that a Van Houtum distribution (or indeed any discrete distribution on the integers) can only be fitted on the first two moments if [3] See also
References1. ^A. Saura (2012), Van Houtumin jakauma (in Finnish). BSc Thesis, University of Helsinki, Finland {{ProbDistributions|discrete-finite}}2. ^J.J. Arts (2009), Efficient optimization of the Dual-Index policy using Markov Chain approximations. MSc Thesis, Eindhoven University of Technology, The Netherlands (Appendix B) 3. ^I.J.B.F. Adan, M.J.A. van Eenige, and J.A.C. Resing. "Fitting discrete distributions on thefirst two moments". Probability in the Engineering and Informational Sciences, 9:623-632,1996. 1 : Discrete distributions |
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