Determine Sample Size to Estimate the Average Parameter of a Heavy Tails Distribution Using Bayesian Methodology

Volume 9, Issue 3, June 2024     |     PP. 57-73      |     PDF (751 K)    |     Pub. Date: May 7, 2024
DOI: 10.54647/mathematics110484    48 Downloads     4686 Views  

Author(s)

Sarmad Abdulkhaleq Salih, University of Al-Hamdaniya , Mosul, Iraq
Omar Ramzi Jasim, University of Al-Hamdaniya , Mosul, Iraq.

Abstract
The generalized modified Bessel distribution is one of the most suitable mixed distributions. It is the result of mixing the normal distribution with the generalized inverse Gaussian distribution.
In this paper, The optimal sample size Analysis has been taken from the generalized modified Bessel population to estimate the mean parameter when the variance and shape parameters are known, using the informative prior information to estimate the mean parameter under the quadratic loss function. Then sampling and non-sampling approaches are used for the estimate of the parameter. Also, it has been noted that the posterior probability distribution for a mean parameter is following a generalized modified Bessel distribution. Through the simulation, we note Bayesian sample size is inversely proportional to the sampling cost (c) per unit.

Keywords
Generalized Modified Bessel Distribution, Quadratic Loss Function, Cost Function, Bayesian Sample Size.

Cite this paper
Sarmad Abdulkhaleq Salih, Omar Ramzi Jasim, Determine Sample Size to Estimate the Average Parameter of a Heavy Tails Distribution Using Bayesian Methodology , SCIREA Journal of Mathematics. Volume 9, Issue 3, June 2024 | PP. 57-73. 10.54647/mathematics110484

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