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

Report Date:

1982-02-01

Pagination or Media Count:

16.0

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 mn 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 - 1n. 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

Subject Categories:

  • Statistics and Probability
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE