Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

Simple, rapid and sensitive spectrophotometric method was proposed for the analysis of metoclopramide hydrochloride (MPH) in pure form as well as in pharmaceutical tablets. The method is based on the diazotization reaction of MPH with sodium nitrite in hydrochloric acid medium to form diazonium salt, which is coupled with 1-naphthol in sodium hydroxide medium to form azo dye, showing absorption maxima at 550 nm. Beer’s law is obeyed in the concentration range of 0.4 – 18 µg mL-1 of MPH with detection limit 0.5448 µg mL-1. The molar absorptivity and Sandell’s sensitivity are 3.4969 × 104 L mol-1 cm-1 and 0.0101 µg cm-2, respectively. The method was successfully applied to the determination of MPH in pharmaceutical tablets with

The changes that have occurred in the business environment and scientific and technological progress, as well as the complexity of administrative problems resulting from its practice of various activities, have led to an increase in the responsibilities entrusted to it, and for the purpose of achieving its strategic objectives, which has made the pillars of corporate governance an inevitable matter required by the nature of modern scientific management of the governorate, the success that companies seek is based on the fertile environment and the dialectical relationship between the individual and the company, and to achieve this success there must be a compatible and harmonious audit environment between the internal and external

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust

Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

The aim of the research was to know the effect of the inquiry wheel model on chemical enlightenment among second-grade middle school female students in government daytime middle and secondary schools. Umm AlQura Middle School was chosen by intentional selection to be its students as the research sample for the academic year (2024-2025). Two groups were chosen, one of which was the experimental group studying using the inquiry wheel model and the other the control group studying in the usual way. The equivalence of the two research groups was verified by a set of variables, which were (chronological age in months, previous information test, Raven's intelligence test, chemical enlightenment scale). As for the research tool, the researchers bu