Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had been applied on IraqHousehold Socio-Economic Survey: IHSES 2012. To measure the preference models used in the research was the use of such standards compared: Root Mean Squares Error: RMSE,Mean Absolute Percentage Error: MAPEand , and Adjusted determinant coefficient: with different weight matrices (binary and modified) take into account the effect of neighborhoods of districts.
The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
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Five heavy metals, namely Cd, Cu, Fe, Mn, and Pb in the surface water and through the water column were studied at 10 selected stations in the Razzazah lake and Karbala drainage canal for the period between November 1990 to October 1991*. pH and total hardness were also measured. Lead was found to be the highest in concentration as overall average values, followed by an manganese, iron, copper then cadmium at the surface as well as along the water column. All the studied metals were below or close to the maximum allowed limits of Iraqi standards for inland water. The spatial and seasonal variations were discussed.
Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
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This study examined the phenomenon of unemployment in Iraq and the extent of the contribution of these loans granted by banks to finance small and medium enterprises in reducing their rates. The temporal boundaries of the study included the period between (2012-2018). The spatial boundaries consisted of random sampling of six Iraqi banks) Where the government banks included (Rafidain, Rasheed and industrial), private banks included (the Iraqi Islamic Bank and the Gulf Commercial Bank and the Bank of the Middle East). In order to achieve the objective of the research in the light of the hypotheses drawn up, the research divided into three topics, the first section highlighting the reality of small and medium enterprises in Iraq and the lo
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Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
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The results show the inability to apply the Taylor rule within inflation and GDP Gaps because the monetary behave is elated from the Iraqi economy.
When applying the Taylor rule to exchange rate with the inflation and the output gap, the results do not match the nominal price announced by the central thing, which proves the lack of commitment by the Central Bank by using the Taylor rule, whether short-run interest rate or exchange rate (Nominal Anchor), so it did not stay to the Iraqi Central Bank only using the principle of Taylor with the expected inflation rate below the level of output (Macro activity) for the separation of monetary behavior from the real one o
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi
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