In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample
... Show MoreThe technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.
There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr
... Show MoreThe research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used
In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.
Here’s a research about epistemology including answer for the most essential questions those which associate with human knowledge, It’s the sources of knowledge and it's pathways depending on showing and criticizing the empirical doctrine represented by John Locke, David Hume and others, not only the empirical doctrine but also the contemporary scientism doctrine the one that characterized by science abilities glorification which is represented by contemporary scientists such as: Stephen Hawking and some few others .The common points between both of the doctrines (scientism and empirical) will be clarified for the reader and also the uncommon ones, ultimately, we will briefly spotlight on the basics of the Islamic vision about knowle
... Show More In this paper the research represents an attempt of expansion in using the parametric and non-parametric estimators to estimate the median effective dose ( ED50 ) in the quintal bioassay and comparing between these methods . We have Chosen three estimators for Comparison. The first estimator is
( Spearman-Karber ) and the second estimator is ( Moving Average ) and The Third estimator is ( Extreme Effective Dose ) . We used a minimize Chi-square as a parametric method. We made a Comparison for these estimators by calculating the mean square error of (ED50) for each one of them and comparing it with the optimal the mean square
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This study is concerned with the estimation of constant and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es
... Show MoreThe research included four topics: the definition of Imam al-Bazzazi, his scientific life, his sheikhs, his students, his writings, his death, and selected issues of his weight in the book of prayer. The Imam al-Bazazi is the son of Muhammad ibnShihabibn Yusuf. He is known as al-Khardizi al-Khawarizmi. The author did not adopt the definitions of language and terminology, and rarely mention the legal evidence adopted by the scholars in their opinions, and only to mention the views only, and the author, may God have mercy on him in his book on the sources of m The Prophet (peace and blessings of Allaah be upon him) said: "The Prophet (peace and blessings of Allaah be upon him) And fall down the order, the third issue, which is to leave the
... Show MoreA simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators
In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.