• Estimating the Burr XII Parame...

Treffer: Estimating the Burr XII Parameters in Constant-Stress Partially Accelerated Life Tests Under Multiple Censored Data

Title:
Estimating the Burr XII Parameters in Constant-Stress Partially Accelerated Life Tests Under Multiple Censored Data
Authors:
CHENG, Yung-Fu, WANG, Fu-Kwun
Source:
Communications in statistics. Simulation and computation. 41(8-10):1711-1727
Publisher Information:
Colchester: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Subject Terms:
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, Inférence paramétrique, Parametric inference, Inférence non paramétrique, Nonparametric inference, Applications, Fiabilité, test de durée de vie, contrôle de la qualité, Reliability, life testing, quality control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Algorithme EM, EM algorithm, Algoritmo EM, Analyse covariance, Covariance analysis, Análisis covariancia, Analyse survie, Survival analysis, Analyse variance, Variance analysis, Análisis variancia, Contrainte mécanique, Mechanical stress, Tensión mecánica, Donnée censurée, Censored data, Donnée observation, Observation data, Dato observación, Erreur quadratique moyenne, Mean square error, Error medio cuadrático, Erreur systématique, Bias, Error sistemático, Essai accéléré, Accelerated test, Ensayo acelerado, Essai endurance, Life test, Prueba duración, Estimation biaisée, Biased estimation, Estimación sesgada, Estimation non paramétrique, Non parametric estimation, Estimación no paramétrica, Estimation paramètre, Parameter estimation, Estimación parámetro, Estimation statistique, Statistical estimation, Estimación estadística, Fiabilité, Reliability, Fiabilidad, Fonction répartition, Distribution function, Función distribución, Fonction vraisemblance, Likelihood function, Función verosimilitud, Intervalle confiance, Confidence interval, Intervalo confianza, Matrice covariance, Covariance matrix, Matriz covariancia, Maximisation, Maximization, Maximización, Maximum vraisemblance, Maximum likelihood, Maxima verosimilitud, Méthode statistique, Statistical method, Método estadístico, Performance algorithme, Algorithm performance, Resultado algoritmo, Régression statistique, Statistical regression, Regresión estadística, Simulation numérique, Numerical simulation, Simulación numérica, Simulation statistique, Statistical simulation, Simulación estadística, Test hypothèse, Hypothesis test, Test hipótesis, Test statistique, Statistical test, Test estadístico, Variance, Variancia, 60E05, 62F03, 62F25, 62G15, 62J10, 62N01, 62N05, Estimation paramétrique, Test multiple, Multiple test, 62N02, Burr XII distribution, Partially accelerated life test, Quasi-Newton algorithm
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Industrial Management, National Taiwan University of Science and Technology, Tawain, Province of China
ISSN:
0361-0918
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=26164018
Rights:
Copyright 2015 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.26164018
Database:
PASCAL Archive

Weitere Informationen

In this article, we present the performance of the maximum likelihood estimates of the Burr XII parameters for constant-stress partially accelerated life tests under multiple censored data. Two maximum likelihood estimation methods are considered. One method is based on observed-data likelihood function and the maximum likelihood estimates are obtained by using the quasi-Newton algorithm. The other method is based on complete-data likelihood function and the maximum likelihood estimates are derived by using the expectation-maximization (EM) algorithm. The variance―covariance matrices are derived to construct the confidence intervals of the parameters. The performance of these two algorithms is compared with each other by a simulation study. The simulation results show that the maximum likelihood estimation via the EM algorithm outperforms the quasi-Newton algorithm in terms of the absolute relative bias, the bias, the root mean square error and the coverage rate. Finally, a numerical example is given to illustrate the performance of the proposed methods.