Title
Self-validating computations of probabilities for selected central and noncentral univariate probability functions
Keywords
Automatic differentiation; Continued fractions; Directed rounding; Interval analysis; Taylor series integration method
Abstract
Self-validating computation based on interval arithmetic can produce computed values with a guaranteed error bound. Such methods are especially useful whenever the computed results must satisfy given accuracy requirements. This article reports methods for obtaining self-validating results when computing probabilities and percentiles of univariate continuous distributions. Probability functions dealt with explicitly in the article are normal, incomplete gamma, incomplete beta, and noncentral chi-squared. © 1994 Taylor & Francis Group, LLC.
Publication Date
1-1-1994
Publication Title
Journal of the American Statistical Association
Volume
89
Issue
427
Number of Pages
878-887
Document Type
Article
Identifier
scopus
Personal Identifier
scopus
DOI Link
https://doi.org/10.1080/01621459.1994.10476820
Copyright Status
Unknown
Socpus ID
21844503454 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/21844503454
STARS Citation
Wang, Morgan C. and Kennedy, William J., "Self-validating computations of probabilities for selected central and noncentral univariate probability functions" (1994). Scopus Export 1990s. 259.
https://stars.library.ucf.edu/scopus1990/259