Treffer: Evaluating best-case and worst-case variances when bounds are available
Title:
Evaluating best-case and worst-case variances when bounds are available
Authors:
Source:
SIAM journal on scientific and statistical computing. 13(6):1347-1360
Publisher Information:
Philadelphia, PA: Society for Industrial and Applied Mathematics, 1992.
Publication Year:
1992
Physical Description:
print, 5 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Bases mathématiques, Mathematical foundations, Analyse circuit, Network analysis, Análisis circuito, Complexité calcul, Computing complexity, Complejidad cálculo, Fiabilité système, System reliability, Fiabilidad sistema, Loi discrète, Discrete distribution, Ley discreta, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Programmation linéaire, Linear programming, Programación lineal, Variable aléatoire, Random variable, Variable aléatoria, Variance, Varianza
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
Univ. North Carolina, dep. operations res., Chapel Hill NC 27599, United States
ISSN:
0196-5204
Rights:
Copyright 1993 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.4630206
Database:
PASCAL Archive
Weitere Informationen
This paper describes procedures for computing the tightest possible best-case and worst-case bounds on the variance of a discrete, bounded, random variable when lower and upper bounds are available for its unknown probability mass function. An example from the application of the Monte Carlo method to the estimation of network reliability illustrates the procedures and, in particular, reveals considerable tightening in the worst-case bound when compared to the trivial worst-case bound based exclusively on range.