Treffer: Goodness-of-Fit Test and Parameter Estimation for a Proportional Odds Model of Random Censorship

Title:
Goodness-of-Fit Test and Parameter Estimation for a Proportional Odds Model of Random Censorship
Authors:
HASAN ABADI, R, DOOSTPARAST, M
Source:
Communications in statistics. Simulation and computation. 41(8-10):1430-1443
Publisher Information:
Colchester: Taylor & Francis, 2012.
Publication Year:
2012
Physical Description:
print, 1/2 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, Théorie des probabilités et processus stochastiques, Probability theory and stochastic processes, Processus particuliers (théorie du renouvellement, processus de renouvellement markoviens, processus semi-markoviens, modèles de la mécanique statistique, applications diverses), Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications), Statistiques, Statistics, Lois de probabilités, Distribution theory, Inférence non paramétrique, Nonparametric inference, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Analyse numérique, Numerical analysis, Análisis numérico, Analyse survie, Survival analysis, Corps nombre, Number field, Campo número, Distribution statistique, Statistical distribution, Distribución estadística, Donnée censurée, Censored data, Echantillon censuré, Censored sample, Muestra censurada, Essai endurance, Life test, Prueba duración, Estimation paramètre, Parameter estimation, Estimación parámetro, Estimation ponctuelle, Point estimation, Estimación puntual, Estimation statistique, Statistical estimation, Estimación estadística, Fiabilité, Reliability, Fiabilidad, Fonction survie, Survival function, Función sobrevivencia, Industrie, Industry, Industria, Ingénierie, Engineering, Ingeniería, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, Méthode statistique, Statistical method, Método estadístico, Méthode stochastique, Stochastic method, Método estocástico, Rapport vraisemblance, Likelihood ratio, Relación verosimilitud, Simulation numérique, Numerical simulation, Simulación numérica, Simulation statistique, Statistical simulation, Simulación estadística, Temps survie, Survival time, Test ajustement, Goodness of fit test, Prueba ajuste, Théorie approximation, Approximation theory, 60K10, 60K20, 62E17, 62F10, 62N01, 62N05, 62Nxx, 62P30, 65C05, Censure aléatoire, Random censorship, Censure proportionnelle, Proportional censorship, Estimation paramétrique, Modèle exponentiel, Exponential model, 62C15, 62F15, 62N02, Generalized likelihood ratio, Interval estimation, Kolmogorov―Smirnov statistics, Proportional odds model, Right randomly censored data
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Statistics, School of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran, Islamic Republic of
ISSN:
0361-0918
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=26163999
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.26163999
Database:
PASCAL Archive

Weitere Informationen

Censored data arise naturally in a number of fields, particularly in problems of reliability and survival analysis. There are several types of censoring, in this article, we will confine ourselves to the right randomly censoring type. Recently, Ahmadi et al. (2010) considered the problem of estimating unknown parameters in a general framework based on the right randomly censored data. They assumed that the survival function of the censoring time is free of the unknown parameter. This assumption is sometimes inappropriate. In such cases, a proportional odds (PO) model may be more appropriate (Lam and Leirng, 2001). Under this model, in this article, point and interval estimations for the unknown parameters are obtained. Since it is important to check the adequacy of models upon which inferences are based (Lawless, 2003, p. 465), two new goodness-of-fit tests for PO model based on right randomly censored data are proposed. The proposed procedures are applied to two real data sets due to Smith (2002). A Monte Carlo simulation study is conducted to carry out the behavior of the estimators obtained.