In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.
The goal of this work is demonstrating, through the gradient observation of a of type linear ( -systems), the possibility for reducing the effect of any disturbances (pollution, radiation, infection, etc.) asymptotically, by a suitable choice of related actuators of these systems. Thus, a class of ( -system) was developed based on finite time ( -system). Furthermore, definitions and some properties of this concept -system and asymptotically gradient controllable system ( -controllable) were stated and studied. More precisely, asymptotically gradient efficient actuators ensuring the weak asymptotically gradient compensation system ( -system) of known or unknown disturbances are examined. Consequently, under convenient hypo
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The Non - Homogeneous Poisson process is considered as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).
This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto , to estimate th
... Show MoreA new mixed ligand complexes have been prepared between 8- hydroxy quinoline and o-hydroxybenzylidene-1-phenyl-2,3-dimethyl-4-amino-3-pyrazolin-5-on with Mn(II),Fe(II),Co(II),Ni(II) and Cu(II) ions . the prepared complexes were isolated and characterized by (FT-IR)and (UV-Vis) spectroscopy. Elemental analysis (C.H.N) Flame atomic absorption technique . in addition to magnetic susceptibility and conductivity measurement.
Four metal complexes mixed ligand of 2-aminophenol (2-AP) and tributylphosphine (PBu3) were produced in aqueous ethanol with (1:2:2) (M:2-AP:PBu3). The prepared complexes were identified by using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition antibacterial activity of the two ligands and mixed ligand complexes oboist three species of bacteria were also examined. The ligands and their complexes show good bacterial activities. From the obtained data the octahedral geometry was suggested for all prepared complexes. Keywords: Mixed ligand complexes, spectral studies, 2-aminophenol, tributylphosphine.
Four metal complexes mixed ligand of 2-aminophenol (2-AP) and tributylphosphine (PBu3) were produced in aqueous ethanol with (1:2:2) (M:2-AP:PBu3). The prepared complexes were identified by using flame atomic absorption, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. In addition antibacterial activity of the two ligands and mixed ligand complexes oboist three species of bacteria were also examined. The ligands and their complexes show good bacterial activities. From the obtained data the octahedral geometry was suggested for all prepared complexes.
Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreCanonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.
In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe
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