Result: Monte-Carlo approximation for probability distribution of monotone Boolean function
Title:
Monte-Carlo approximation for probability distribution of monotone Boolean function
Authors:
Source:
Special Issue on The Fourth St. Petersburg Workshop on SimulationJournal of statistical planning and inference. 132(1-2):21-31
Publisher Information:
Amsterdam; Lausanne; New York,NY: Elsevier Science, 2005.
Publication Year:
2005
Physical Description:
print, 5 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, 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, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Théorie de la fiabilité. Renouvellement des équipements, Reliability theory. Replacement problems, Décision statistique, Statistical decision, Decisión estadística, Estimation moyenne, Mean estimation, Estimación promedio, Estimation sans biais, Unbiased estimation, Estimación insesgada, Fiabilité système, System reliability, Fiabilidad sistema, Fonction booléenne, Boolean function, Función booliana, Fonction logique, Logical function, Función lógica, Forme canonique, Canonical form, Forma canónica, Forme normale, Normal form, Forma normal, Loi probabilité, Probability distribution, Ley probabilidad, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode statistique, Statistical method, Método estadístico, 06E30, 60E05, 60K10, 60K20, 62E17, 62J10, 62N05, 62P30, 65C05, Estimation variance, Variance estimation, Evaluation fiabilité, Reliability evaluation, 65C05: 90B25 Logical functions, Monte-Carlo method
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Mathematical Support of Transport System Management, Riga Technical University, 1 Kalku St., 1658 Riga, Latvia
ISSN:
0378-3758
Rights:
Copyright 2005 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
Operational research. Management
Operational research. Management
Accession Number:
edscal.16705692
Database:
PASCAL Archive
Further Information
The new method for probability of the value 1 evaluation for monotone Boolean function (for example for system reliability) is proposed. The method is based on a presentation of the function by its canonical disjunctive normal form. Monte-Carlo procedure assumes random choice of this form terms. Their arithmetical mean gives approximation for the probability of the value 1. Such an estimator is unbiased. The variance of this estimator has been calculated. It is shown that proposed method has less variance in comparison with the crude Monte-Carlo method.