In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes

Cancer is one of the dangerous diseases that afflict a person through injury to cells and tissues in the body, where a person is vulnerable to infection in any age group, and it is not easy to control and multiply between cells and spread to the body. In spite of the great progress in medical studies interested in this aspect, the options for those with this disease are few and difficult, as they require significant financial costs for health services and for treatment that is difficult to provide.

This study dealt with the determinants of liver cancer by relying on the data of cancerous tumours taken from the Iraqi Center for Oncology in the Ministry of Health 2017. Survival analysis has been used as a m

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

The penalized least square method is a popular method to deal with high dimensional data ,where  the number of explanatory variables is large than the sample size . The properties of  penalized least square method are given high prediction accuracy and making estimation and variables selection

 At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

المستخلص
، ( اب ( ١٩٢٢ ô یدتھ ارض الیب ô ي قص ô وت ،ف ô زي الی ô اعر الانجلی ô یھدف ھذا البحث الى بیان مدى تأكید الش
ن ô ة م ô ان والطبیع ô ین الانس ô ت ب ô ا ربط ô ي لطالم ô ة ،الت ô على الحاجة الملحة للانسان الحدیث لاسترجاع الصلة الحمیم
ة ô ي بمثاب ô ة ھ ô ان الثلاث ô ذه الارك ô ین ھ ô ة ب ô ة الموثق ô ذه العلاق ô رى .ان ھ ô ة اخ ô ن جھ ô جھة ، وبین الانسان والاسطورة م
ات ô ي الثقاف ô ة ف ô وس الدینی ô وبة والطق ô اطیر الخ

The expansion of the social media environment has created its own linguistic realities which involve more colloquial communication and practical employment of language. This research focuses on nominalizations in detail, which are originally formed words that have been changed for a noun role. These nominalizations are examined within the context of Facebook posts. The research aims to discover the various nominalizations used and how often they appear in a large sample of data from Public Facebook Posts Corpora. Computational linguistics opened new fields of study and enabled researchers to study large amounts of data easily, making it easier to identify patterns. Two computational methods of identifying nominalization in a large dataset w

The research Reviews the sides of highlight importance of the Nano-Accounting which doing the accounting performance functions fully computerized without the intervention of an accountant, to solve the problem of not keeping up the  rationalization of recording and accounting systems, with the rationalization of production which fully computerized.(be invisible and hidden accounting), resulting by linking or interaction of the accounting, additive production system represented three-dimensional printers, open source and recycling. That which result the rationalizing the facilities of production, organization and self-control which derived nanotechnology idea, which aims to minimize materials and change it properties, then view the a