A comparison of bayes estimators for the parameter of rayleigh distribution with simulation

Abstract EN

A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered.

Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution.

We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large).

And Bayes estimators for the parameter is derived under a squared error loss function and weighted squared error loss function) in the cases of the three different sets of prior distributions .Simulations is employed to obtain results.

And determine the best estimator according to the smallest value of mean squared error and weighted mean squared error.

We found that the best estimation for the parameter ( θ) for all sample sizes (n) , when the double prior distribution for θ is SRIG - the natural conjugate family of priors distribution with values (a=5, b=0.5, α =8, β =0.5) and (a=8, b=1, α =5, β =1) for the true value of θ ( θ  0.5 and 1) respectively .Also ,we obtained the best estimation for θ when the double prior distribution for θ is the natural conjugate family of priors-non-informative distribution with values( α =0.5, β =5, c=1) for the true value of θ (θ 1.5).