This 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 across districts in Iraq. Considering poverty rate as the dependent variable with eight explanatory variables. The analysis confirmed spatial dependence among regions, as indicated by the estimated values of the spatial correlation parameter (ρ) across different scenarios. It made clear that poverty rates are heavily influenced by spatial dependence and that failing to consider this could result in the loss of important information regarding the phenomenon and eventually impair the accuracy of statistical index estimation. This enhancement offers suggestions for methods of reducing poverty.
Zirconia ceramic restoration (ZCR) has a higher fracture incidence rate than metal ceramic restoration. Different surface treatments were used to improve fracture performance of ZCR such as grit blasting (GB) by aluminium oxide powder. This type of surface treatment generate residual stresses on veneering ceramic causing crack initiation and ending with a fracture. In order to overcome the stress generated by GB, zirconia surface coating is used as a surface treatment to improve fracture resistance and to accommodate stresses along the ZCR layers. Fifty zirconia ceramic crowns were fabricated and divided according to the type of surface treatment into three groups; the first group is (ZG), involving 20 cores were coated with a mixture of pa
... Show MoreIn this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending
In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho
... Show MoreIn this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application
Inflation is one of the important issues that the economic authorities in all countries of the world care about, where the loss of money for its function is one of the most important and largest inflationary effects that this phenomenon leaves on the economy, and Iraq, like other countries, has had its share of the problem of inflation for a long time due to the circumstances that He went through it, whether it was the wars he fought or the economic blockade that was imposed on him in the nineties of the last century. Economically, the problem of inflation is addressed through the use of fiscal policy tools, including tax increases in order to abso
... Show MoreInflation is one of the important issues that the economic authorities in all countries of the world care about, where the loss of money for its function is one of the most important and largest inflationary effects that this phenomenon leaves on the economy, and Iraq, like other countries, has had its share of the problem of inflation for a long time due to the circumstances that He went through it, whether it was the wars he fought or the economic blockade that was imposed on him in the nineties of the last century. Economically, the problem of inflation is addressed through the use of fiscal policy tools, including tax increases in order to abso
... Show MoreThe study aimed to determine the extent of market knowledge in the companies researched, as if market knowledge is qualified to lead the companies researched to achieve marketing performance , for this purpose, formulated hypotheses of the study in three hypotheses, the first major hypothesis "there is a correlation with significance of market knowledge to improve the marketing performance , "while the second major hypothesis, "there is a significant moral influence of market knowledge to improve the marketing performance " these hypotheses targeting to determine the role played by market knowledge in the leadership of companies researched to achieve improvement in marketing perfor
... Show MoreThe unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I
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