Abstract:
This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.
The comparison was done by simulation using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood with sample size (n = 30) is the best to represent the maternal mortality data after it has been reliance value param
... Show MoreA novel azo dye ligand namely (2-(pyridin-3-yldiazenyl)naphthalen-1-ol (HPYNA), was synthesized by the coupling reaction of diazonium salt of 3-aminopyridine with naphthol. The palladium(II) complex for HPYNA ligand was prepared by reacting palladium(II) ions with the HPYNA ligand. These synthesized compounds were characterized using different techniques, including mass, 1H-NMR, infrared, and UV-Vis spectroscopy. The infrared results show that the azo ligand reacts as a bidentate via the oxygen atom of phenol and nitrogen atom of the azo group. The palladium(II) complex is square-planer with diamagnetic properties depending on the results of electronic transitions and magnetic sensitivity. The HPYNA ligand and palladium complex show
... Show MorePOSSIBILITY OF APPLICATION THE BALANCED SCORECARD IN THE IRAQI INDUSTRIAL COMPANIES: A PROPOSED MODEL
The purpose of this research is to determine the extent to which independent auditors can audit the requirements of e-commerce related to (infrastructure requirements, legislation and regulations, tax laws, and finally human cadres). To achieve this, a questionnaire was designed for auditors. Numerous statistical methods, namely arithmetic mean and standard deviation, have been used through the implementation of the Statistical Packages for Social Sciences (SPSS) program.
The research has reached several results, the most important of which are: There are noobstacles to enabling the auditor to audit the application of the e-commerce requirements as well as the respective(infrastructure requirements, legislation and regulations, t
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Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted
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The extremes effects in parameters readings which are BOD (Biological Oxygen Demands) and DO(Dissolved Oxygen) can caused error estimating of the model’s parameters which used to determine the ratio of de oxygenation and re oxygenation of the dissolved oxygen(DO),then that will caused launch big amounts of the sewage pollution water to the rivers and it’s turn is effect in negative form on the ecosystem life and the different types of the water wealth.
As result of what mention before this research came to employees Streeter-Phleps model parameters estimation which are (Kd,Kr) the de oxygenation and re oxygenation ratios on respect
... Show MoreIn this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.
In this paper has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi
... Show MoreThis research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
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