Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson

This research deals with the role that the media can play in spreading awareness, culture and sound behavior among members of society, due to its ability to reach the largest number of individuals; its wide spread within society; and the moral responsibility of the media in consolidating the components of civil peace. The media works on forming intellectual convictions and behavioral attitudes by publishing opinions and ideas, introducing them to people's awareness and enhancing them in the practice of their daily lives, he was its media medium. Sociologists and psychologists confirm that the media. The significance of the research comes due to the broadening of violence and sectarian fighting; the absence of a culture of civil social pe

In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

The importance of media coverage in the war remains dependent on many indicators for its success, the most important is to have qualified reporters who carry the war news professionally. The idea of this research is to determine the role played by war correspondents working on Iraqi satellite channels during the war against ISIS.
The researcher has chosen ( 40 ) reporters those who was able to contact them and prepared a questionnaire for them to study their situations. Also, he chose an intentional sample from Baghdad audience on condition they should be informed by the performance of the reporters in the satellite channels applying the hypotheses of the theory of depending upon media.
The most important results reached by the re

The issue of sports media and its role in winning sports and non-sports fans and unifying them towards various issues and events is one of the important topics that have begun to occupy many countries and governments in the world and allocate appropriate spaces for it and provide it with sufficient funds and budgets to advance this reality...

Especially since the concept of the sports official has It changed a lot and turned into an economic concept rather than a sport one through the investment in the field of sports and the entry of capital and contributes to the prosperity of the countries interested in this field.

It is important that includes profit and loss in addition to knowing how to employ and win the masses and e

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear