• PARUL YADAV
• UMA SRIVASTAVA

The Generalized Compound Rayleigh Distribution (GCRD) is a special case of the three parameter Burr type XII distribution. This uni-ַmodal hazard function is generalized and a flexible parametric model is thus constructed, which embeds the compound Rayleigh model, by adding shape parameter. The main objective of this paper is determine the best estimator for the three parameter Generalized Compound Rayleigh Distribution assuming all the parameters unknown. The methods under consideration are Maximum Likelihood Estimation and Bayesian Estimation underline Loss Function. Lindley Approximation is use to obtain the Approximate Bayes Estimate of GCRD assuming all the parameters unknown under LINEX LOSS FUNCTION. We have studied the sensitivity of the Approximate Bayes Estimate of the model and presented a numerical study to illustrate the above technique on generated observations. The comparison is done by R-programming.

Maximum Likelihood Estimation, Bayesian Approximation, Linex Loss Function, Lindley Approximation

"APPROXIMATE BAYES ESTIMATE FOR THE PARAMETERS OF GENERALIZED COMPOUND RAYLEIGH DISTRIBUTION UNDER LINEX LOSS FUNCTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.k230-k242, June-2023, Available :http://www.jetir.org/papers/JETIR2306A28.pdf

"APPROXIMATE BAYES ESTIMATE FOR THE PARAMETERS OF GENERALIZED COMPOUND RAYLEIGH DISTRIBUTION UNDER LINEX LOSS FUNCTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppk230-k242, June-2023, Available at : http://www.jetir.org/papers/JETIR2306A28.pdf