Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Error (MCE) criterion was used to compare the two models, leading to the conclusion that the Nadaraya-Watson (NW) circular model outperformed the parametric model in estimating the parameters of the circular regression model. Research, Practical & Social Implications: The recommendation emphasized using the Nadaraya-Watson nonparametric smoothing method to capture the nonlinearity in the data. Originality/value: The results indicated that the Nadaraya-Watson circular model (NW) outperformed the parametric model. Paper type Research paper.
Typhoid fever (TF) is a systemic infection caused by Salmonella Typhi (Salmonella Enterica) transmitted through contaminated water, food, or contact with infected individuals. In various infectious diseases, blood viscosity (BV) is affected by changes in hemoglobin concentrations and acute phase reactants. Inflammatory responses can lead to elevated plasma protein levels and further affect BV. This study aimed to investigate BV changes in patients with acute TF. A cross-sectional study was performed involving 55 patients with acute TF compared to 38 healthy controls. BV and inflammatory parameters were measured in both groups. TF patients showed reduced blood cells compared to healthy controls (p=0.001). Additionally, plasma total protein (
... 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.
This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
The aim of the research was to assess effects of short and long-period exposure to radiation from mobile phone on blood indices in experimental rats. In this study forty mature female rats were used; the animals were divided into two experimental group, each group consists of twenty animals. Short-period group of rats were exposed to cell phone radiation for different duration 30 m, 60 m, and 90 m per day for six weeks. Long-period group of rats were exposed to radiation from mobile phone for different duration 2h, 4h, and 6h per day for three months. The study noticed that there was significant (P≥0.05) elevation in total white blood cells and the study demonstrated significant increment (P≥0.05) in percentage of
... Show MoreChemiluminescenc (CL), light emitted during chemical reaction, is one of the accurate methods used to detect directly oxygen free radicals. In this study, luminol was used as CL detector, to detect the concentration of free radicals formed in whole blood exposed to high power microwave pulses. The changes in the intensity of CL signal gives a clear relation between the concentration of free radicals formed by radiation in blood and changes in blood properties such as hemolysis of blood cells. This is done by measuring the electrical sytoplsimic electrical properties, the results are substituted in Maxwell-Wagner equation, to obtain electrical conductivity of cytoplasm, which is 18.3 ms/cm, while at suspension med
... Show MoreThe present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.
Knowledge represents the foundation stone for the work of all organizations, are working who leads the thinking of individuals is the ability that leads to behavior based on rationality, it is the work that creates value to the organization and thus gain access to performance winning where that knowledge is a new type of capital based on the thought and experience and is the so-called intellectual capital, which is renewable and is constantly evolving. The study sought to explain the role of the climax knowledge in achieving the highest levels of performance Organizational and then access to the performance winning in educational organizations the study sample, was found to be a co
... Show MoreThe 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 the comparison between binary lo
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