QE-Bayesian and E-Bayesian Estimation of the Frechet Model

Reyad, Hesham; Younis, Adil Mousa; Ahmed, S. E.

doi:10.9734/bjmcs/2016/29231

“…Nasir and Aslam [13] utilized a Bayesian technique to estimate the parameter of the Fréchet distribution. Reyad et al [14] established QE-Bayes and E-Bayes estimates for the scale parameters associated with the Fréchet distribution. Recent developments have introduced various extensions to the Fréchet distribution.…”

Section: Introductionmentioning

confidence: 99%

Properties and Maximum Likelihood Estimation of the Novel Mixture of Fréchet Distribution

Phaphan,

Abdullahi,

Puttamat

2023

Symmetry

2

0

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In recent decades, there have been numerous endeavors to develop a novel category of survival distributions possessing enhanced flexibility through the extension of existing distributions. This article constructs and validates the statistical properties of a novel survival distribution in order to obtain an alternative distribution that is suitable for analyzing survival data by presenting the novel mixture of the Fréchet distribution along with statistical properties such as the probability density function (PDF), cumulative distribution function (CDF), rth ordinary moment, skewness, kurtosis, moment-generating function, mean, variance, mode, survival function, hazard function, and asymptotic behavior, as well as constructing the estimators of the unknown parameter by employing the expectation-maximization (EM) algorithm, and simulated annealing. Additionally, the performance of the proposed estimators was compared with bias, mean squared errors (MSE), and simulated variances, and given an illustrative example of the proposed distribution to the survival data set in order to show that the proposed distribution is appropriate for the right-skewed data. This will be extremely advantageous in survival analysis.

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“…Nasir and Aslam [12] utilized a Bayesian technique to estimate the parameter of the Fréchet distribution. Reyad et al [13] established QE-Bayes and E-Bayes estimates for the scale parameters associated with the Fréchet distribution. Recent developments have introduced various extensions to the Fréchet distribution.…”

Section: Introductionmentioning

confidence: 99%

Properties and Maximum Likelihood Estimation of the Novel Mixture of Fréchet Distribution

Phaphan,

Abdullahi,

Puttamat

2023

Preprint

2

0

View full text Add to dashboard Cite

In recent decades, there have been numerous endeavors to develop a novel category of survival distributions possessing enhanced flexibility through the extension of existing distributions. This article constructs and validates the statistical properties of a novel survival distribution in order to obtain an alternative distribution that is suitable for analyzing survival data by presenting the novel mixture of the Fréchet distribution along with statistical properties such as the probability density function (PDF), cumulative distribution function (CDF), rth ordinary moment, skewness, kurtosis, moment-generating function, mean, variance, mode, survival function, hazard function, and asymptotic behavior, as well as constructing the estimators of the unknown parameter by employing the expectation-maximization (EM) algorithm, and simulated annealing. Additionally, the performance of the proposed estimators was compared with bias, mean squared errors (MSE), and simulated variances, and given an illustrative example of the proposed distribution to the survival data set in order to show that the proposed distribution is appropriate for the right-skewed data. This will be extremely advantageous in survival analysis.

show abstract