The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of this paper is to suggest a new hybrid estimator obtained by an ad-hoc algorithm which relies on data driven strategy that overcomes outliers. While the minor goal is to introduce a new employment of an unweighted estimation method named "winsorization" which is a good method to get robustness in regression estimation via special technique to reduce the effect of the outliers. Another specific contribution in this paper is to suggest employing "Kernel" function as a new weight (in the scope of the researcher's knowledge).Moreover, two weighted estimations are based on robust weight functions named "Cauchy" and "Talworth". Simulations have been constructed with contamination levels (0%, 5%, and 10%) which associated with sample sizes (n=40,100). Real data application showed the superior performance of the suggested method compared with other methods using RMSE and R2 criteria.
In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-
... Show MoreSemiconductor laser is used in processing many issues related to the scientific, military, medical, industrial and agricultural fields due to its unique properties such as coherence and high strength where GaN-based components are the most efficient in this field. Current technological developments mention to the strong connection of GaN with sustainable electronic and optoelectronic devices which have high-efficiency. The threshold current density of Al0.1Ga0.9N/GaN triple quantum well laser structure was investigated to determine best values of the parameters affecting the threshold current density that are well width, average thickness of active region, cavity length, reflectivity of cavity mirrors and optical confinement factor. The opt
... Show MoreBenign prostatic hyperplasia (BPH) is one of the most common disease and major cause of morbidity in elderly men which may lead to bladder outflow obstruction and lower urinary tract symptoms (LUTS). Although sex steroid hormones play fundamental roles in prostate growth, their clinical significance is not completely clear. In the present study we assessed whether serum hormones levels as markers of prostate disease. This study includes (40) patients with benign prostatic hypertrophy and (40) control group with age rang (41-79) and (42-71) years respectively. The following biochemical investigations have been studied: Testosterone, Estradiol (E2), and Prostatic Specific Antigen (PSA) levels using ELISA method which correlated with t
... Show MoreSome experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.
The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show MoreBy driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root gives invertible model and when the sign is negative means the root gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when
Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f
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