Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use a difference based through the use of biased estimators, in order to get less biased and variance estimators therefor we used difference based estimator liu and difference based almost unbiased liu estiomator. throughout studying simulation based upon mean square error, we concluded that difference based almost unbiased liu estiomator is better than difference based estimator liu since it has the smallest mean square error after that we estimate nonparametric component so removing parametric component and estimated Nonparametric using k-nearest neighbor smoother.
The fractional order partial differential equations (FPDEs) are generalizations of classical partial differential equations (PDEs). In this paper we examine the stability of the explicit and implicit finite difference methods to solve the initial-boundary value problem of the hyperbolic for one-sided and two sided fractional order partial differential equations (FPDEs). The stability (and convergence) result of this problem is discussed by using the Fourier series method (Von Neumanns Method).
In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved
... Show MoreThis paper assesses the impact of changes and fluctuations in bank deposits on the money supply in Iraq. Employing the research constructs an Error Correction Model (ECM) using monthly time series data from 2010 to 2015. The analysis begins with the Phillips-Perron unit root test to ascertain the stationarity of the time series and the Engle and Granger cointegration test to examine the existence of a long-term relationship. Nonparametric regression functions are estimated using two methods: Smoothing Spline and M-smoothing. The results indicate that the M-smoothing approach is the most effective, achieving the shortest adjustment period and the highest adjustment ratio for short-term disturbances, thereby facilitating a return
... Show MoreA simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.
The method is utilized to predict
... Show MoreThis paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the cov
... Show MoreThe Islamic Banks including the Iraqi ones are often resorted to support their governance frameworks in order to improve its competitiveness in their communities. Where, those banks are looking for activities that enhance their governance; one of these activities is Shariah Audit that provided the auditing capabilities to face of developmental challenges and increase competitiveness. Therefore, the content of this paper, discusses know-how to use the Shariah Audit and its references in support of the Shariah Governance in the Iraqi Isla
... Show MoreIn this study, silver-tungsten oxide core–shell nanoparticles (Ag–WO3 NPs) were synthesized by pulsed laser ablation in liquid employing a (1.06 µm) Q-switched Nd:YAG laser, at different Ag colloidal concentration environment (different core concentration). The produced Ag–WO3 core–shell NPs were subjected to characterization using UV–visible spectrophotometry, X-ray diffraction (XRD), transmission electron microscopy (TEM), energy-dispersive spectroscopy, electrical analysis, and photoluminescence PL. The UV–visible spectra exhibited distinct absorption peaks at around 200 and 405 nm, which attributed to the occurrence of surface Plasmon reson
In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes