Preferred Language
Articles
/
jeasiq-1091
Estimate the Nonparametric Regression Function Using Canonical Kernel
...Show More Authors

    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 estimators (Simple and Multiple linear regressions).

 

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Existence, Uniqueness and Approximate Controllability of Impulsive Fractional Nonlinear Control System with Nonsingular Kernel
...Show More Authors

     The main aim of this work is to investigate the existence and approximate controllability of mild solutions of impulsive fractional nonlinear control system with a nonsingular kernel in infinite dimensional space. Firstly, we set sufficient conditions to demonstrate the existence and uniqueness of the mild solution of the control system using the Banach fixed point theorem. Further, we prove the approximate controllability of the control system using the sequence method.

View Publication Preview PDF
Scopus Crossref
Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
strong criminal capabilities، Using simulation .
...Show More Authors

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

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compared Some Estimators Ordinary Ridge Regression And Bayesian Ridge Regression With Practical Application
...Show More Authors

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 metho

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
The Use of Parametric and Nonparametric Methods to Study the Effects of Smoking on High-Density Lipoprotein Cholesterol
...Show More Authors

Analysis of variance (ANOVA) is one of the most widely used methods in statistics to analyze the behavior of one variable compared to another. The data were collected from a sample size of 65 adult males who were nonsmokers, light smokers, or heavy smokers. The aim of this study is to analyze the effects of cigarette smoking on high-density lipoprotein cholesterol (HDL-C) level and determine whether smoking causes a reduction  in this level, by using the completely randomized design (CRD) and Kruskal- Wallis method. The results showed that the assumptions of the one- way ANOVA are not satisfied, while, after transforming original data by using log transformation, they are satisfied. From the results, a significantly

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison Between Two Approaches (MLE &DLS) to Estimate Frechet Poisson Lindley Distribution Compound by Using Simulation
...Show More Authors

  In this paper simulation technique plays a vital role to compare between two approaches Maximum Likelihood method and Developed Least Square method to estimate the parameters of Frechet Poisson Lindley Distribution Compound. by coding using Matlab software program. Also, under different sample sizes via mean square error. As the results which obtain that Maximum Likelihood Estimation method is better than Developed Least Square method to estimate these parameters to the proposed distribution.

View Publication Preview PDF
Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Parameters of General Linear Model in Presence of Heteroscedastic Problem and High Leverage Points
...Show More Authors

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
...Show More Authors

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

... Show More
Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Estimation of Cutoff Values by Using Regression Lines Method in Mishrif Reservoir/ Missan oil Fields
...Show More Authors

Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Predicting COVID-19 in Iraq using Frequent Weighting for Polynomial Regression in Optimization Curve Fitting
...Show More Authors

     The worldwide pandemic Coronavirus (Covid-19) is a new viral disease that spreads mostly through nasal discharge and saliva from the lips while coughing or sneezing. This highly infectious disease spreads quickly and can overwhelm healthcare systems if not controlled. However, the employment of machine learning algorithms to monitor analytical data has a substantial influence on the speed of decision-making in some government entities.        ML algorithms trained on labeled patients’ symptoms cannot discriminate between diverse types of diseases such as COVID-19. Cough, fever, headache, sore throat, and shortness of breath were common symptoms of many bacterial and viral diseases.

This research focused on the nu

... Show More
View Publication Preview PDF
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
...Show More Authors

This 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 More
View Publication Preview PDF