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

    In the presence of multi-collinearity problem, the parameter estimation method based on the ordinary least squares procedure is unsatisfactory. In 1970, Hoerl and Kennard insert analternative method labeled as estimator of ridge regression.

In such estimator, ridge parameter plays an important role in estimation. Various methods were proposed by many statisticians to select the biasing constant (ridge parameter). Another popular method that is used to deal with the multi-collinearity problem is the principal component method. In this paper,we employ the simulation technique to compare the performance of principal component estimator with some types of ordinary ridge regression estimators based on the value of t

Monthly rainfall data of Baghdad meteorological station were taken to study the time behavior of these data series. Significant fluctuation,very slight increasing trend and significant seasonality were noticed. Several ARIMA models were tested and the best one were checked for the adequacy. It is found that the SEASONAL ARIMA model of the orders SARIMA(2,1,3)x(0,1,1) is the best model where the residual of this model exhibits white noise property, uncorrelateness and they are normally distributed. According to this model, rainfall forecast for four years was also achieved and showing similar trend and extent of the original data.

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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

      It is common that extraterrestrial solar radiation R_a value lessen due to the interaction with atmosphere components to result a net solar radiation R_n value about one third of R_a for most measurements on earth. Net solar radiation had major impact on air temperature (T_o) value statement. So, its estimation is crucial for analyzing the interaction of (atmosphere-vegetation-soil).

Many methodologies available for this aim directly (with radiometer) or indirectly (with air temperature-based formula or soil plus air temperatures-based formula). The peak influences of global warming phenomenon were in eighties decade of the last century, yielding Iraq R_n rates to get cl

Ceramic art associated with urban growth in the cities, it overlapped with architectural construction, the increasing of population, urban growth, knowledge, and civilization was considered ceramic arts as an important aesthetically architecturally complement in the cities, including those in the squares and architectural institutions in the city of Baghdad .the title (Ceramic Art and Urban Planning in the City of Baghdad) the problem was its wonders : 1- Does ceramic monuments suited their locations in the city of Baghdad with the architectural planning urban of the city.2- Does the recipient interacted with these monuments and the reasons of their existence. Then the aim: knowing the relationship of the ceramic monuments with the urban

Multilevel models are among the most important models widely used in the application and analysis of data that are characterized by the fact that observations take a hierarchical form, In our research we examined the multilevel logistic regression model (intercept random and slope random model) , here the importance of the research highlights that the usual regression models calculate the total variance of the model and its inability to read variance and variations between levels ,however in the case of multi-level regression models, the calculation of  the total variance is inaccurate and therefore these models calculate the variations for each level of the model, Where the research aims to estimate the parameters of this m

Three hundred Iraqi people participated in demographic and attitudes study about red and white meat consumption. The mean age of the participants was 50 SD ± 11 years (mean 30-72); 51% were females and 49% males, mostly in forties who lived ≥ 5 years in Baghdad. The results showed that 80% of individuals prefer red meat. A 90% of people prefer fresh meat compared to frozen and processed meat. A 60% of people buy meat from popular markets. Nearly 87% of respondents believe the improving of livestock sector is essential and 80% of people confirmed there are obstacles to development this sector. An 80% of participates thought the reasons of the high prices of local fresh meat is the lack of planning and support to livestock sector. A survey