检索结果-内蒙古大学图书馆

Estimation and Prediction for the Generalized Half Normal Distribution under Hybrid Censoring

JOURNAL OF TESTING AND EVALUATION 2020年第2期48卷 1071-1094页

作者： Sultana, Farha Tripathi, Yogesh Mani Indian Inst Technol Patna Dept Math Bihta 801106 Bihar India

In this article, we make estimation and prediction inferences for the generalized half normal distribution. The maximum likelihood and Bayes estimators of unknown parameters are obtained based on hybrid Type I censored samples. We obtain asymptotic intervals using the observed Fisher information matrix and also construct bootstrap intervals of unknown parameters. Bayes estimators are obtained under the squared error loss function using different approximation methods. We also construct the highest posterior density intervals of unknown parameters. Further one- and two-sample predictors and prediction intervals of censored observations are discussed. A Monte Carlo simulation study is conducted to compare the performance of the proposed methods. We further analyze a real data set for illustrative purposes. Finally, conclusions are presented.

关键词： Bayes estimates expectation-maximization algorithm hybrid Type I censoring importance sampling scheme Bayesian prediction Tierney and Kadane method

来源：评论

学校读者我要写书评

暂无评论

Estimation for the exponentiated Weibull model with adaptive Type-II progressive censored schemes

引用

APPLIED MATHEMATICAL MODELLING 2016年第2期40卷 1180-1192页

作者： AL Sobhi, Mashail M. Soliman, Ahmed A. Umm Al Qura Univ Dept Math Mecca Saudi Arabia Islamic Univ Dept Math Madina Saudi Arabia

In reliability and life testing experiments, the censoring scheme which can balance between the total time spent for the experiment, the number of units used and the efficiency of statistical inference based on the results of the experiment is desirable. An adaptive Type-II progressive censoring schemes have been shown to be useful in this case. This article deals with the problem of estimating parameters, reliability and hazard functions of the two-parameter exponentiated Weibull distribution, under adaptive progressive Type II censoring samples using Bayesian and non-Bayesian approaches. Maximum likelihood estimates (M LEs) are proposed for unknown quantities. The asymptotic normality of the MLEs are used to compute the approximate confidence intervals for these quantities, parametric bootstrap confidence intervals are also constructed. Markov Chain Monte Carlo (MCMC) samples using importance sampling scheme are used to produce the Bayes estimates and the credible intervals for the unknown quantities. A real-life data-set is analyzed to illustrate the proposed methods of estimation. Finally, results from simulation studies assessing the performance of the maximum likelihood and Bayes estimators are discussed. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Exponentiated Weibull distribution An adaptive Type-II progressive censoring scheme Bayesian non-Bayesian approaches Parametric bootstrap confidence intervals Markov chain Monte Carlo importance sampling scheme

来源：评论

学校读者我要写书评

暂无评论

Estimation using hybrid censored data from a two-parameter distribution with bathtub shape

引用

COMPUTATIONAL STATISTICS & DATA ANALYSIS 2013年 67卷 268-281页

作者： Rastogi, Manoj Kumar Tripathi, Yogesh Mani Indian Inst Technol Patna Dept Math Patna 800013 Bihar India

The problem of estimating unknown parameters of a two-parameter distribution with bathtub shape is considered under the assumption that samples are hybrid censored. The maximum likelihood estimates are obtained using an EM algorithm. The Fisher information matrix is obtained as well and the asymptotic confidence intervals are constructed. Further, two bootstrap interval estimates are also proposed for the unknown parameters. Bayes estimates are evaluated under squared error loss function. Approximate explicit expressions for these estimates are derived using the Lindley method as well as using the Tierney and Kadane method. An importance sampling scheme is then proposed to generate Markov Chain Monte Carlo samples which have been used to compute approximate Bayes estimates and credible intervals for the unknowns. A numerical study is performed to compare the proposed estimates. Finally, two data sets are analyzed for illustrative purposes. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Bayes estimates EM algorithm Hybrid Type I censoring importance sampling scheme Lindley approximation method Square error loss Tierney and Kadane method

来源：评论

学校读者我要写书评

暂无评论

Estimation for an inverted exponentiated Rayleigh distribution under type II progressive censoring

引用

JOURNAL OF APPLIED STATISTICS 2014年第11期41卷 2375-2405页

作者： Rastogi, Manoj Kumar Tripathi, Yogesh Mani Indian Inst Technol Patna Dept Math Patna 800013 Bihar India

In this paper, we consider estimation of unknown parameters of an inverted exponentiated Rayleigh distribution under type II progressive censored samples. Estimation of reliability and hazard functions is also considered. Maximum likelihood estimators are obtained using the Expectation-Maximization (EM) algorithm. Further, we obtain expected Fisher information matrix using the missing value principle. Bayes estimators are derived under squared error and linex loss functions. We have used Lindley, and Tiernery and Kadane methods to compute these estimates. In addition, Bayes estimators are computed using importance sampling scheme as well. Samples generated from this scheme are further utilized for constructing highest posterior density intervals for unknown parameters. For comparison purposes asymptotic intervals are also obtained. A numerical comparison is made between proposed estimators using simulations and observations are given. A real-life data set is analyzed for illustrative purposes.

关键词： Bayes estimator HPD interval importance sampling scheme Lindley method maximum likelihood estimator progressive type II censoring Tierney and Kadane method

来源：评论

学校读者我要写书评

暂无评论

Parameter and reliability estimation for an exponentiated half-logistic distribution under progressive type II censoring

引用

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2014年第8期84卷 1711-1727页

作者： Rastogi, Manoj Kumar Tripathi, Yogesh Mani Indian Inst Technol Dept Math Patna 800013 Bihar India

In this article, we deal with a two-parameter exponentiated half-logistic distribution. We consider the estimation of unknown parameters, the associated reliability function and the hazard rate function under progressive Type II censoring. Maximum likelihood estimates (M LEs) are proposed for unknown quantities. Bayes estimates are derived with respect to squared error, linex and entropy loss functions. Approximate explicit expressions for all Bayes estimates are obtained using the Lindley method. We also use importance sampling scheme to compute the Bayes estimates. Markov Chain Monte Carlo samples are further used to produce credible intervals for the unknown parameters. Asymptotic confidence intervals are constructed using the normality property of the MLEs. For comparison purposes, bootstrap-p and bootstrap-t confidence intervals are also constructed. A comprehensive numerical study is performed to compare the proposed estimates. Finally, a real-life data set is analysed to illustrate the proposed methods of estimation.

关键词： bootstrapping progressive type II censoring maximum likelihood estimates importance sampling scheme Bayes estimates credible intervals Lindley approximation method

来源：评论

学校读者我要写书评

暂无评论

importance sampling FOR INDICATOR MARKOV CHAINS

IMPORTANCE SAMPLING FOR INDICATOR MARKOV CHAINS

引用

2010 Winter Simulation Conference

作者： Giesecke, Kay Shkolnik, Alexander D. Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA Stanford Univ Inst Computat & Math Engn Stanford CA 94305 USA

ISBN: (纸本)9781424498642

We consider a continuous-time, inhomogeneous Markov chain M taking values in {0, 1}(n). Processes of this type arise in finance as models of correlated default timing in a portfolio of firms, in reliability as models of failure timing in a system of interdependent components, and in many other areas. We develop a logarithmically efficient importance sampling scheme for estimating the tail of the distribution of the total transition count of M at a fixed time horizon.

关键词： Markov processes correlated default timing model estimation theory finance firm portfolio importance sampling importance sampling scheme indicator Markov chains investment tail distribution estimation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：