On the Independence of Jeffreys’ Prior for Truncated-Exponential Skew-Symmetric Models

Subject Areas : International Journal of Industrial Mathematics

سعید میرزاده ¹ , انیس ایرانمنش ² , احسان ارمز ³

1 - Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
2 - Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
3 - Department of Mathematics and Statistics, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

Received: 2020-11-19 Accepted : 2021-10-02 Published : 2022-01-01

Keywords: Bayesian estimator, Posterior existence, Truncated exponential skew-logistic distributions, Simulation, Truncated-exponential skew-symmetric distributions, Jeffreys’ prior,

Abstract :

We study the independent Jeffreys' prior of the unknown location, scale and skewness parameters of truncated-exponential skew-symmetric distributions(TESSD). We show that this prior is symmetric and improper but it yields a proper posterior distribution for some densities. A simulation study using Monte Carlo methods is presented to compare the efficiency of Bayesian estimators in TESSD with Azzalinis' skew models under square error loss and Linex loss functions.

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