ScholarLens Back to search
2022•DOAJ (DOAJ: Directory of Open Access Journals)Open access

Bayesian Shrinkage Approach in Weibull Type -II Censored Data Using Prior Point Information

Gyan Prakash, D.C. Singh

Open full text 16 citations

Abstract

In the present paper we study the performance of the Bayes Shrinkage estimators for the scale parameter of the Weibull distribution under the squared error loss and the LINEX loss functions in the presence of a prior point information of the scale parameter when Type -II censored data are available. The properties of the minimax estimators are also discussed.

About this research paper

What this paper is about

In the present paper we study the performance of the Bayes Shrinkage estimators for the scale parameter of the Weibull distribution under the squared error loss and the LINEX loss functions in the presence of a prior point information of the scale parameter when Type -II censored data are available. The properties of the minimax estimators are also discussed.

Why it matters

OpenAlex reports 16 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In the present paper we study the performance of the Bayes Shrinkage estimators for the scale parameter of the Weibull distribution under the squared error loss and the LINEX loss functions in the presence of a prior point information of the scale parameter when Type -II censored data are available. The properties of the minimax estimators are also discussed.

Key concepts: Weibull distribution, Bayesian probability, Shrinkage, Statistics, Computer science, Point (geometry), Data mining, Mathematics

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Bayesian Shrinkage Approach in Weibull Type -II Censored Data Using Prior Point Information — Research Paper | ScholarLens