Amal S. Hassan¹, Ehab M. Almetwally^2,*, Gamal M. Ibrahim³

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 337-358, 2021, DOI:10.32604/cmc.2021.013971

Abstract In this paper, an attempt is made to discover the distribution of COVID-19 spread in different countries such as; Saudi Arabia, Italy, Argentina and Angola by specifying an optimal statistical distribution for analyzing the mortality rate of COVID-19. A new generalization of the recently inverted Topp Leone distribution, called Kumaraswamy inverted Topp–Leone distribution, is proposed by combining the Kumaraswamy-G family and the inverted Topp–Leone distribution. We initially provide a linear representation of its density function. We give some of its structure properties, such as quantile function, median, moments, incomplete moments, Lorenz and Bonferroni curves, entropies measures and stress-strength reliability. Then,… More >

Farouq Mohammad A. Alam¹, Sharifah Alrajhi¹, Mazen Nassar^1,2, Ahmed Z. Afify^3,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2185-2202, 2021, DOI:10.32604/cmc.2021.015089

Abstract The main objective of this paper is to discuss a general family of distributions generated from the symmetrical arcsine distribution. The considered family includes various asymmetrical and symmetrical probability distributions as special cases. A particular case of a symmetrical probability distribution from this family is the Arcsine–Gaussian distribution. Key statistical properties of this distribution including quantile, mean residual life, order statistics and moments are derived. The Arcsine–Gaussian parameters are estimated using two classical estimation methods called moments and maximum likelihood methods. A simulation study which provides asymptotic distribution of all considered point estimators, 90% and 95% asymptotic confidence intervals are… More >

Ramadan A. ZeinEldin^1,2, Christophe Chesneau^3,*, Farrukh Jamal⁴, Mohammed Elgarhy⁵, Abdullah M. Almarashi⁶, Sanaa Al-Marzouki⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 791-819, 2021, DOI:10.32604/cmes.2021.012169

Abstract Understanding a phenomenon from observed data requires contextual and efficient statistical models. Such models are based on probability distributions having sufficiently flexible statistical properties to adapt to a maximum of situations. Modern examples include the distributions of the truncated Fréchet generated family. In this paper, we go even further by introducing a more general family, based on a truncated version of the generalized Fréchet distribution. This generalization involves a new shape parameter modulating to the extreme some central and dispersion parameters, as well as the skewness and weight of the tails. We also investigate the main functions of the new… More >

Usman Shahzad^1,2,*, Ishfaq Ahmad¹, Ibrahim Mufrah Almanjahie^3,4, Nadia H. Al Noor⁵, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3013-3028, 2021, DOI:10.32604/cmc.2021.014101

Abstract Variance is one of the most important measures of descriptive statistics and commonly used for statistical analysis. The traditional second-order central moment based variance estimation is a widely utilized methodology. However, traditional variance estimator is highly affected in the presence of extreme values. So this paper initially, proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics (L-location, L-scale, L-CV) and auxiliary information. It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than… More >

Ali Algarni, Muhammad Qaiser Shahbaz^*

Computer Systems Science and Engineering, Vol.36, No.1, pp. 83-100, 2021, DOI:10.32604/csse.2021.014342

Abstract Probability distributions have been in use for modeling of random phenomenon in various areas of life. Generalization of probability distributions has been the area of interest of several authors in the recent years. Several situations arise where joint modeling of two random phenomenon is required. In such cases the bivariate distributions are needed. Development of the bivariate distributions necessitates certain conditions, in a field where few work has been performed. This paper deals with a bivariate beta-inverse Weibull distribution. The marginal and conditional distributions from the proposed distribution have been obtained. Expansions for the joint and conditional density functions for… More >

Shaheena Khanum¹, Muhammad Adeel Ashraf², Asim Karim¹, Bilal Shoaib³, Muhammad Adnan Khan⁴, Rizwan Ali Naqvi⁵, Kamran Siddique⁶, Mohammed Alswaitti^6,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2165-2181, 2021, DOI:10.32604/cmc.2020.013646

Abstract Glycation is a non-enzymatic post-translational modification which assigns sugar molecule and residues to a peptide. It is a clinically important attribute to numerous age-related, metabolic, and chronic diseases such as diabetes, Alzheimer’s, renal failure, etc. Identification of a non-enzymatic reaction are quite challenging in research. Manual identification in labs is a very costly and time-consuming process. In this research, we developed an accurate, valid, and a robust model named as Gly-LysPred to differentiate the glycated sites from non-glycated sites. Comprehensive techniques using position relative features are used for feature extraction. An algorithm named as a random forest with some preprocessing… More >

Yanping Wang^1,2, Zhengqiang Feng¹, Almaspoor Zahra^3,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 919-929, 2021, DOI:10.32604/cmc.2020.012261

Abstract In recent years, there has been an increased interest among the researchers to propose new families of distributions to provide the best fit to lifetime data with monotonic (increasing, decreasing, constant) and non-monotonic (unimodal, modified unimodal, bathtub) hazard functions. We further carry this area of research and propose a new family of lifetime distributions called a new logarithmic family via the T-X family approach. For the proposed family, explicit expressions for some mathematical properties along with the estimation of parameters through Maximum likelihood method are discussed. A sub-model, called a new logarithmic Weibull distribution is taken up. The proposed model… More >

Rashad Bantan¹, Amal S. Hassan², Mahmoud Elsehetry^{3, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2169-2187, 2020, DOI:10.32604/cmc.2020.011497

Abstract In this article, we offer a new adapted model with three parameters, called Zubair Lomax distribution. The new model can be very useful in analyzing and modeling real data and provides better fits than some others new models. Primary properties of the Zubair Lomax model are determined by moments, probability weighted moments, Renyi entropy, quantile function and stochastic ordering, among others. Maximum likelihood method is used to estimate the population parameters, owing to simple random sample and ranked set sampling schemes. The behavior of the maximum likelihood estimates for the model parameters is studied using Monte Carlo simulation. Criteria measures… More >

B. Chandrasekhar¹

CMES-Computer Modeling in Engineering & Sciences, Vol.9, No.3, pp. 243-254, 2005, DOI:10.3970/cmes.2005.009.243

Abstract In this work, a novel numerical technique is presented to calculate the acoustic fields scattered by three dimensional rigid bodies of arbitrary shape using the method of moment's solution procedure. A new set of basis functions, namely, Node based basis functions are developed to represent the source distribution on the surface of rigid body and the same functions are used as testing functions as well. Both single layer formulation and double layer formulations are numerically solved using the same basis functions. The surface of the body is modeled by triangular patch modeling. Numerical technique presented in this paper, using these… More >

Liming Yang¹, Yongping Gao², Qun Sun³

CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.6, pp. 493-506, 2015, DOI:10.3970/cmes.2015.104.493

Abstract Minimax probability machine (MPM) has been recently proposed and shown its advantage in pattern recognition. In this paper, we present a new minimax probabilistic approach (MPA),which can provide an explicit lower bound on prediction accuracy. Applying the Chebyshev-Cantelli inequality, the MPA is posed as a second order cone program formulation and solved effectively. Following that, this method is exploited directly to recognize the purity of hybrid seeds using near-infrared spectroscopic data. Experimental results in different spectral regions show that the proposed MPA is competitive with the existing minimax probability machine and support vector machine in generalization, while requires less computational… More >