Bayesian estimation for Rayleigh distribution based on ranked set sampling

Year 2017, Volume: 5 Issue: 4, 97 - 106, 01.10.2017

Saeid Tahmasebi , Elham Haji Hosseini Ali Akbar Jafari

Abstract

The Rayleigh distribution is an
important model in applications such as noise theory, height of the sea waves
and wave length. In this paper, we provide Bayesian estimation for a parameter
of the Rayleigh distribution based on simple random sample (SRS) and ranked set
sampling (RSS) and maximum ranked set sampling procedure with unequal samples
(MRSSU) in two cases, one cycle and m-cycle. We also obtain the Bayes
estimators by using square-root inverted-gamma and Jeffreys prior under squared
error loss function and general entropy loss function and LINEX function.
Finally, we compute the bias and mean squared error of an estimator under
squared error and compare its with the corresponding RSS and MRSSU through
Monte Carlo simulations.

Keywords

Ranked set sampling, Rayleigh distribution, Conjugate prior, Jeffreys prior

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