BAYESIAN PREDICTION OF PROGRESSIVELY FIRST-FAILURE-CENSORED ORDER STATISTICS BASED ON k-RECORD VALUES FROM WEIBULL DISTRIBUTION

Autor:	AHMADİ, Mohammad Vali, DOOSTPARAST, Mahdi
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	Bayesian prediction k-record Progressive first-failure censoring Weibull distribution
Zdroj:	Volume: 11, Issue: 1-2 12-28 Istatistik Journal of The Turkish Statistical Association
ISSN:	1300-4077
Popis:	Prediction on the basis of censored data has an important role in lifetime studies. This paper discusses Bayesian two-sample prediction of progressively firrst-failure-censored order statistics coming from a future sample based on observed k-record values from two-parameter Weibull distribution. Bayesian interval predictions are obtained based on a continuous-discrete joint prior for the unknown two parameters. Moreover, Bayesian point predictors are investigated under symmetric and asymmetric loss functions. Finally, the estimated risks of various point predictors obtained are compared using the Monte Carlo method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=tubitakulakb::4bbfe223b3a8b3136ac44414f118f488 https://dergipark.org.tr/tr/pub/ijtsa/issue/38356/446758 Zobrazit plný text záznamu