We have presented the distribution of the exponentiated expanded power function (EEPF) with four parameters, where this distribution was created by the exponentiated expanded method created by the scientist Gupta to expand the exponential distribution by adding a new shape parameter to the cumulative function of the distribution, resulting in a new distribution, and this method is characterized by obtaining a distribution that belongs for the exponential family. We also obtained a function of survival rate and failure rate for this distribution, where some mathematical properties were derived, then we used the method of maximum likelihood (ML) and method least squares developed (LSD) to estimate the parameters and because of the nonlinear relationship between the parameters, numerical algorithms were used to find the estimates of the two methods. They are Newton-Raphson (NR) and Nelder mead (NM) algorithms to improve the estimators, and a Monte Carlo simulation experiment was conducted to evaluate the performance of the two algorithms' estimates, and the average integrated error criterion (IMSE) was used to compare the survival function estimates and the failure rate. The results showed the efficiency of the maximum likelihood method estimates and least squares developed using the two algorithms (NR, NM) where their results were close, and this shows the new distribution efficiency (EEPF) for modeling survival data.
This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The
... Show MoreIs in this research review of the way minimum absolute deviations values based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.
The research aims to apply the activities of the green value chain as one of the modern administrative techniques that economic units resort to develop solutions to the pollution problems that occur due to the activity of economic units and their products that may cause damage to the environment as well as the waste of natural resources and to identify the production of environmentally friendly products and reduce the costs of environmental failure of both types Internal and external that may be borne by economic units such as taxes, fines and compensation due to non- observance of environmental requirements and the preservation of human health and protection of the environment.To achieve the goal of the research, the researchers re
... Show MoreReceipt date:12/7/2020 accepted date:24/1/2021 Publication date:31/12/2021
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The constant characteristic of international relations is the constant change due to political, economic and military developments in addition to technology, and this in turn has led to many transformations in the concept of power, its uses, and the elements that form power and its distribution, and according to those variables, the concept of power has shifted from hard to soft, up to smart powe
... Show MoreThis research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa
... Show MoreThe current study was conducted to find out the effect of the sediment source (sedimentary of Iraqi-Iranian borderline and Tigris River) on the content and distribution of feldspar minerals and their effect on the optical properties of these minerals in some soils of Wasit and Maysan province. Eight pedons were chosen to represent the study area, five of them represented sediments coming from the borderline, which included pedons of (Badra, Taj Al-Din, Al-Shihabi, Jassan, and Galat), while two of them represent the sediments of the Tigris River (Essaouira, Al-Dabouni). Finally, the pedon of Ali Al-Gharbi represented the mixing area of sediments of all the torrents coming from borderline and the sediments of the Tigris River. The diagnostic
... Show MoreThis research aims to suggest formulas to estimate carry-over effects with two-period change-over design, and then, all other effects in the analysis of variance of this design, and find the efficiency of the two-period change-over design relative to another design (say, completely randomized design).
As the process of estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .
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