Accession Number : ADA111967

Title :   Sampling from a Discrete Distribution While Preserving Monotonicity.

Descriptive Note : Technical rept.,

Corporate Author : NORTH CAROLINA UNIV AT CHAPEL HILL CURRICULUM IN OPERATIONS RESEARCH AND SYSTEMS ANALYSIS

Personal Author(s) : Fishman,George S ; Moore,Louis R , III

PDF Url : ADA111967

Report Date : Feb 1982

Pagination or Media Count : 16

Abstract : This paper describes a cutpoint method for sampling from an n-point discrete distribution that preserves the monotone relationship between a uniform deviate and the random variate it generates. This property is useful when developing a sampling plan to reduce variance in a Monte Carlo or simulation study. The alias sampling method generally lacks this property and requires 2n storage locations while the proposed cutpoint sampling method requires m+n storage locations, where m donotes the number of cutpoints. The expected number of comparisons with this method is derived and shown to be bounded above by (m + n - 1/n. The paper describes an algorithm to implement the proposed method as well as two modifications for cases in which n is large and possibly infinite. (Author)

Descriptors :   *Probability distribution functions, Statistical samples, Random variables, Sampling, Algorithms

Subject Categories : Statistics and Probability
      Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE