The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

The researcher studied transportation problem because it's great importance in the country's economy. This paper which ware studied several ways to find a solution closely to the optimization, has applied these methods to the practical reality by taking one oil derivatives which is benzene product, where the first purpose of this study is, how we can reduce the total costs of transportation for product of petrol from warehouses in the province of Baghdad, to some stations in the Karsh district and Rusafa in the same province. Secondly, how can we address the Domandes of each station by required quantity which is depending on absorptive capacity of the warehouses (quantities supply), And through r

This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may