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Compared Some Estimators Ordinary Ridge Regression And Bayesian Ridge Regression With Practical Application
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Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square method, We will use the simulation to compare these methods using the mean squares error criteria. The method of biased  gave good results by using sizes different samples.

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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Electronics,computer Networking And Applied Mathematics
Comparison of Some Estimator Methods of Regression Mixed Model for the Multilinearity Problem and High – Dimensional Data
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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.

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Publication Date
Wed Mar 09 2022
Journal Name
Journal Of Craniofacial Surgery
The Use of Osseodensification for Ridge Expansion and Dental Implant Placement in Narrow Alveolar Ridges: A Prospective Observational Clinical Study
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The osseodensification (OD) drilling technique was suggested as an alveolar ridge expansion technique, so the aim of this prospective clinical study was to evaluate the amount of bone expansion obtained by the OD drilling technique and its effect on implant stability in patients with narrow alveolar ridges. The width of the alveolar ridge was measured at the crest before and after implant site preparation, whereas the implant stability was measured using Osstell Beacon implant stability quotient (ISQ). The ISQ values were recorded immediately postoperatively and after 16 weeks. Twenty-three patients were included; they received 40 implants. The mean (± standard deviation [SD]) amount of expansion was 1.29 (± 0.41) mm, and the difference b

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimators for the Parameter of the Inverted Exponential Distribution Under different Double informative priors
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In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential distribution by using Bayes estimation ,will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Bayes Estimators for the parameter of Rayleigh Distribution with Simulation
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   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

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Publication Date
Fri Jul 23 2021
Journal Name
International Journal Of Dentistry
Predicting Canine and Premolar Mesiodistal Crown Diameters Using Regression Equations
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Objectives. The current study aimed to predict the combined mesiodistal crown widths of maxillary and mandibular canines and premolars from the combined mesiodistal crown widths of maxillary and mandibular incisors and first molars. Materials and Methods. This retrospective study utilized 120 dental models from Iraqi Arab young adult subjects with normal dental relationships. The mesiodistal crown widths of all teeth (except the second molars) were measured at the level of contact points using digital electronic calipers. The relation between the sum mesiodistal crown widths of the maxillary and mandibular incisors and first molars and the combined mesiodistal crown widths of the maxillary and mandibular canines and premolars was as

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
discriminate analysis and logistic regression by use partial least square
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Abstract

   The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search th

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Publication Date
Tue Dec 16 2008
Journal Name
Journal Of Planner And Development
Housing finance and housing needs in Iraq with reference to some Arab experiences
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the financial resources represent a basic factor of production ;It is obvious that the housing sector needs the resources to finance the building operation to produce all the housing units. Finance is the cornerstone of any housing strategy , as its successes dependent on the success of the financing methods and the creation of charnels and effective methods for the provision of the required finances for both individuals and instantly concerned with the production of housing units. The kinds of financial institutions vary from one country to another according to the nature of the economic and financial system. The lending conditions also vary as well as the capital cost of the housing units needed The housing operations is concer

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Estimate the Nonparametric Regression Function Using Canonical Kernel
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    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

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Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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