In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.
The aim of this research is to solve a real problem in the Department of Economy and Investment in the Martyrs establishment, which is the selection of the optimal project through specific criteria by experts in the same department using a combined mathematical model for the two methods of analytic hierarchy process and goal programming, where a mathematical model for goal programming was built that takes into consideration the priorities of the goal criteria by the decision-maker to reach the best solution that meets all the objectives, whose importance was determined by the hierarchical analysis process. The most important result of this research is the selection of the second pro
... Show MoreWe have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.
The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable. &nb
... Show MoreAtheists have spread in the modern era, so that atheism has become a bad phenomenon in the world in general and in Islamic societies in particular, so the research aims to study the individual and social effects left by atheism on the atheists themselves, and the research included multiple axes: atheism linguistically and idiomatically, atheism in the Qur’an Noble and Modern (and Contemporary) Atheism Statistics: and the reasons for atheism: Studying the phenomenon of atheism in Iraq as a model, then studying the effects of atheism: on the individual first, then atheism and its impact on society, then the conclusion, recommendations, sources and references
When exercising their authority in the jurisprudence, judges are subject to a set of restrictions that they must adhere to, as they do not want their jurisprudence to be accepted and welcomed by law practitioners in general, and legal scholars in particular, and in contrast to it, the arrows of criticism and defamation will extend to that jurisprudence, and then they will have to reverse them . Perhaps the most important of those restrictions imposed on judges is their observance of justice between the parties to the lawsuit through their lack of bias for one of the parties at the expense of the other, in addition to their observance of public order and public morals, as well as their observance of the legal texts that they work under its u
... Show MoreIt is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases : first, in real data; and secondly, after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.
In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.
تتحقق اهداف الدول عبر توظيف امكانياتها ومواردها ، وهذا التوظيف يقترن بوسائل مختلفة باختلاف الامكانيات المتاحة. وتتفاوت هذه الوسائل ما بين الاكراه والترغيب ، واحياناً من الممكن استخدام كلا الوسيلتين ، وتندرج هذه الوسائل من حيث تصنيفها ضمن نوعين رئيسين هما: القوة الصلبة ]القوة العسكرية والاقتصادية[ والقوة الناعمة ]استخدام جميع ادوات الترغيب وتسخيرها من اجل ان تُعجب بها الدول الاخرى وتنصاع
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