Bayes Estimation under Balanced Loss Functions

We derive Bayes estimators of reliability and the parameters of a two- parameter geometric distribution under the general entropy loss, minimum expected loss and linex loss, functions for a noninformative as well as beta prior from multiply Type II censored data. We have studied the robustness of the estimators using simulation and we observed that the Bayes estimators of reliability and the parameters of a two-parameter geometric distribution under all the above loss functions appear to be robust with respect to the correct choice of the hyperparameters a(b) and a wrong choice of the prior parameters b(a) of the beta prior.

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Posterior risks of estimates under balanced loss functions for progressive Type II censored data

Model Assisted Statistics and Applications ◽

10.3233/mas-140313 ◽

2015 ◽

Vol 10 (1) ◽

pp. 73-87

Author(s):

D.R. Barot ◽

M.N. Patel

Keyword(s):

Censored Data ◽

Loss Functions ◽

Type Ii ◽

Progressive Type ◽

Type Ii Censored Data ◽

Balanced Loss Functions

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Bayes estimation based on -record data from a general class of distributions under balanced type loss functions

Journal of Statistical Planning and Inference ◽

10.1016/j.jspi.2008.07.008 ◽

2009 ◽

Vol 139 (3) ◽

pp. 1180-1189 ◽

Cited By ~ 36

Author(s):

Jafar Ahmadi ◽

Mohammad Jafari Jozani ◽

Éric Marchand ◽

Ahmad Parsian

Keyword(s):

General Class ◽

Bayes Estimation ◽

Loss Functions ◽

Record Data

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Bayesian Inference of Burr Type VIII Distribution Based on Censored Samples

International Journal of Mathematics and Mathematical Sciences ◽

10.1155/2014/519469 ◽

2014 ◽

Vol 2014 ◽

pp. 1-21

Author(s):

Navid Feroz

Keyword(s):

Bayesian Inference ◽

Loss Function ◽

Simulation Study ◽

Bayes Estimation ◽

Loss Functions ◽

Quadratic Loss ◽

Bayes Estimators ◽

Type Viii ◽

Censored Samples ◽

Made In

This paper is concerned with estimation of the parameter of Burr type VIII distribution under a Bayesian framework using censored samples. The Bayes estimators and associated risks have been derived under the assumption of five priors and three loss functions. The comparison among the performance of different estimators has been made in terms of posterior risks. A simulation study has been conducted in order to assess and compare the performance of different estimators. The study proposes the use of inverse Levy prior based on quadratic loss function for Bayes estimation of the said parameter.

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