Statistical Inference on Type II Topp Leone Generalized Inverted Exponential Distribution with Some Applications on Real Data
DOI:
https://doi.org/10.29020/nybg.ejpam.v18i4.5860Keywords:
Bayesian estimation; Generalized Inverted Exponential Dis tribution; Type II Topp– Leone. loss function; Jeffrey’s prior and Quasi prior; loss function; Mont Carlo simulationAbstract
In this article, different Bayes techniques are applied to derive the estimators of the additional shape parameter (α) of Type II Topp Leone Generalized In verted Exponential (TIITLGIE) distribution in the case of complete samples.
Two cases were adopted: (a) Bayesian estimation with non-informative priors (Jeffrey’s prior and Quasi prior under three different risk functions: Relative Quadratic loss function (Rq), Precautionary loss function (P) and Entropy loss function (E)). (b) Bayesian estimation with informative prior depending on standard Bayesian technique is derived under three types of loss functions: Squared Error loss function (SE), Linear Exponential loss function (LINEX) and General Entropy loss function (GE). Mont Carlo simulation study was conducted to find the estimators and compare between these techniques and the Non-Bayesian techniques. Some results are given and showed the best estimation method. Numerical computations and real data sets are given to illustrate these results
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