Rana A. Bakoban, Maha A. Aldahlan^*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 129-142, 2022, DOI:10.32604/iasc.2022.018041

Abstract In this article, Bayesian techniques are adopted to estimate the shape parameter of the generalized inverted exponential distribution (GIED) in the case of complete samples. Normal approximation, Lindley’s approximation, and Tierney and Kadane’s approximation are used for deriving Bayesian estimators. Different informative priors are considered, such as Jeffrey’s prior, Quasi prior, modified Jeffrey’s prior, and the extension of Jeffrey’s prior. Non-informative priors are also used, including Gamma prior, Pareto prior, and inverse Levy prior. The Bayesian estimators are derived under the quadratic loss function. Monte Carlo simulations are carried out to make a comparison among estimators based on the mean… More >

Amer I. Al-Omari¹, Amal S. Hassan², Heba F. Nagy², Ayed R. A. Al-Anzi^3,*, Loai Alzoubi¹

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3795-3811, 2021, DOI:10.32604/cmc.2021.019061

Abstract This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution. Assuming that the observed samples are taken from the upper record ranked set sampling (URRSS) and upper record values (URV) schemes. Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error, linear exponential and precautionary loss functions, in addition, we obtain Bayesian credible intervals. The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution. Then, the behavior of the estimates is examined at various record values. The output of the study… More >

Muhammad Aslam Mohd Safari¹, Nurulkamal Masseran^2,*, Muhammad Hilmi Abdul Majid²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2807-2824, 2021, DOI:10.32604/cmc.2021.018815

Abstract In modeling reliability data, the exponential distribution is commonly used due to its simplicity. For estimating the parameter of the exponential distribution, classical estimators including maximum likelihood estimator represent the most commonly used method and are well known to be efficient. However, the maximum likelihood estimator is highly sensitive in the presence of contamination or outliers. In this study, a robust and efficient estimator of the exponential distribution parameter was proposed based on the probability integral transform statistic. To examine the robustness of this new estimator, asymptotic variance, breakdown point, and gross error sensitivity were derived. This new estimator offers… More >

Abdullah Ali H. Ahmadini¹, Amal S. Hassan², Rokaya E. Mohamed^3,*, Shokrya S. Alshqaq⁴, Heba F. Nagy⁵

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 131-146, 2021, DOI:10.32604/iasc.2021.017652

Abstract In this research article, we propose and study a new model the so-called Marshal-Olkin Kumaraswamy moment exponential distribution. The new distribution contains the moment exponential distribution, exponentiated moment exponential distribution, Marshal Olkin moment exponential distribution and generalized exponentiated moment exponential distribution as special sub-models. Some significant properties are acquired such as expansion for the density function and explicit expressions for the moments, generating function, Bonferroni and Lorenz curves. The probabilistic definition of entropy as a measure of uncertainty called Shannon entropy is computed. Some of the numerical values of entropy for different parameters are given. The method of maximum likelihood… More >

H. Zheng¹, X. Peng^1,2,3, N. Hu^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.86, No.6, pp. 505-532, 2012, DOI:10.3970/cmes.2012.086.505

Abstract The static and kinematic shakedown of a functionally graded plate (FGP) is analyzed. The FGP is subjected coupled constant mechanical load and cyclically varying temperature. The FGP is composed of elastoplastic matrix and elastic particles, with the particle volume fraction varying along its thickness. The thermal and mechanical properties and their distributions are evaluated with a mean filed approach, which is based on the Eshelby's inclusion theory and takes into account directly the interaction between particles. The FGP is assumed to be separated into a number of thin layers, the thermal and mechanical properties in the thickness direction of each… More >