IIARD International Institute of Academic Research and Development

INTERNATIONAL JOURNAL OF APPLIED SCIENCES AND MATHEMATICAL THEORY (IJASMT )

E- ISSN 2489-009X
P- ISSN 2695-1908
VOL. 9 NO. 2 2023
DOI: https://doi.org/10.56201/ijasmt.v9.no2.2023.pg44.53

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Assessment of Scale Variable of Log-Gamma Distribution: A Bayesian Technique

Gambo S. A. , Hussain Y. , Abba S. A. , Isa I., Luqman A

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Abstract

The aim of this paper is to estimate scale parameter ? of Log Gamma distribution by using inverse Gamma and inverse Chi-Square priors. The measures of loss function; Squared error loss function (SELF) and Quadratic loss function (QLF) are compared through the estimates of the scale parameter ? for best results. Wolfram Mathematica 11 was used for the analysis. The results showed that estimates of the scale parameter decrease with increase in sample size tending to the actual value of the scale parameter. This indicates an increase in the estimate of shape parameter under loss functions being considered. However, inverse chi square prior outperforms inverse gamma prior. The posterior risks for QLF are least compared to those under SELF. The Quadratic loss function therefore, appeared to be better than Squared error loss function.

Informative Prior, Posterior, Loss Function and Wolfram Mathematica 11

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