In this paper we suggest new method to estimate the missing data in bivariate normal distribution and compare it with Single Imputation method (Unconditional mean and Conditional mean) by using simulation.
In this paper we suggest new method to estimate the missing data in bivariate normal distribution and compare it with Single Imputation method (Unconditional mean and Conditional mean) by using simulation.
Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreThe analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.
Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.
The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.
In the analysis of d
... Show MoreThe research has been concerned with the modalities of foreign trade payments (foreign trade financing), and made an accounting comparison between them to choose the best way to pay for the imported goods (payment of the real values of imported goods), given the importance of the impact of this activity on the national economy of all countries of the world, especially Iraq for the adoption of a very large amount of imported goods to meet the requirements of the people, which require the flow of huge amounts of foreign currency outside Iraq to pay for these goods, and therefore dealing incorrectly with it leads to the destruction of the national economy and the spread of a number of negative social and economic phenomena of
... Show Moreتستخدم تقنيات التصنيفِ ًبصورة واسعة جدا في كثير من المجالات التطبيقية. ولاسيما في المجالات الاقتصادية والتحليلات المالية كما في عِلْمِ تحليل الزبونِ التنبؤيِpredictive customer analytics ، الذي يتضمن ذلك الإمتلاكِ، المقايضة، إحتكار وإحراز الإئتمانِ والجباياتِ. إنّ هدفَ أيّ نموذج تصنيفِ هو أَنْ يُصنّفَ َ المشاهدات في مجموعتين أَو أكثرِ للوصول الى التنبؤ بنتيجةً ترتبط بكُلّ مشاهدة ومثا
... Show MoreTransforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr
... Show MoreThis research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
... Show MoreIn this article, the partially ordered relation is constructed in geodesic spaces by betweeness property, A monotone sequence is generated in the domain of monotone inward mapping, a monotone inward contraction mapping is a monotone Caristi inward mapping is proved, the general fixed points for such mapping is discussed and A mutlivalued version of these results is also introduced.
In this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes n=40,60,100,variances used σ2=0.5,1,1.5 the results for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the
... Show MorePerformance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.
To give aclear picture about performance must be used compound measure, that was best than single measure.
Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.