Staff Members - Benha University
Estimations and Prediction from the Inverse Rayleigh Model Based on Lower Record Statistics
Life Science Journal • 2012
Publication Information
Authors
A.I. Shawky and M. M. Badr
Keywords
Bayesian inference; Squared error loss function; LINEX loss function; Maximum likelihood function;
Reliability; Failure rate; Record values; Inverse Rayleigh distribution
Journal
Life Science Journal
Publisher
Not Available
Volume
9
Issue
1
Pages
985-990
publication.type
International
Paper Link
Not Available
Supplementary Materials
Not Available
Abstract
Abstract: This article considers estimation of the unknown parameters for the inverse Rayleigh distribution (IRD)
based on lower record values. We consider the maximum likelihood (ML) and Bayesian inference of the unknown
parameters of the model, as well as the reliability and cumulative hazard rate functions. The Bayes estimators are
obtained relative to both symmetric (squared error) and asymmetric (linear exponential (LINEX)) loss functions. It is
noticed that the symmetric and asymmetric Bayes estimators are obtained in closed forms. Bayesian prediction
interval of the future record values are obtained as well. Finally, practical examples using real record values are
given to illustrate the application of the results
based on lower record values. We consider the maximum likelihood (ML) and Bayesian inference of the unknown
parameters of the model, as well as the reliability and cumulative hazard rate functions. The Bayes estimators are
obtained relative to both symmetric (squared error) and asymmetric (linear exponential (LINEX)) loss functions. It is
noticed that the symmetric and asymmetric Bayes estimators are obtained in closed forms. Bayesian prediction
interval of the future record values are obtained as well. Finally, practical examples using real record values are
given to illustrate the application of the results