This study is about finding the estimation of tow equations, the comparative has been done between the estimations  by using seemingly unrelated regression equations for the variable and random error has been distribution with poisson and the variable and random error has been distribution with normal and the method by using oldenary lest square.

While in the application side, we have estimated the parameter of investment specification function for the sector of agriculture with the industry sector is enabled us to obtain an estimation efficiency for the model of seemingly unrelated Poisson regression equation.

المستخلص

The paired sample t-test for testing the difference between two means in paired data is not robust against the violation of the normality assumption. In this paper, some alternative robust tests have been suggested by using the bootstrap method in addition to combining the bootstrap method with the W.M test. Monte Carlo simulation experiments were employed to study the performance of the test statistics of each of these three tests depending on type one error rates and the power rates of the test statistics. The three tests have been applied on different sample sizes generated from three distributions represented by Bivariate normal distribution, Bivariate contaminated normal distribution, and the Bivariate Exponential distribution.

The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation techniq

المستخلـص

تم في هذا البحث دراسة الطرائق اللامعلمية الرتيبة لتقدير دالة الأنحدار اللامعلمي، ومعالجة القيم الشاذة الموجودة في دالة الأنحدار اللامعلمي لجعل الدالة رتيبة (متزايدة أو متناقصة).

لذا سنقوم أولاً بتقدير دالة الأنحدار اللامعلمي بإستخدام ممهد Kernel ومن ثم تطبيق الطرائق الرتيبة لجعل الدالة متزايدة إذ سنتناول ثلاث طرائق للتقدير:-

1- طريقة ste

ABSTRACT

In this research been to use some of the semi-parametric methods the based on the different function penalty as well as the methods proposed by the researcher  because these methods work to estimate and variable selection of significant at once for single index model including (SCAD-NPLS method , the first proposal SCAD-MAVE method , the second proposal  ALASSO-MAVE method ) .As it has been using a method simulation time to compare between the semi-parametric estimation method studied , and various simulation experiments to identify the best method based on the comparison criteria (mean squares error(MSE) and average  mean squares error (AMSE)).

And the use

المقدمة ومنهجية البحث

تتفق أغلب الأدبيات ومنها المحاسبية, بأن الخطوة الأولى في وضع وتقييم أي نظام إداري أو محاسبي هي في صياغة أهداف ذلك النظام لما لذلك من أهمية في توفير معيار للحكم على كفاءة التطبيق من عدمه.

وتعرف الأهداف بأنها (النهايات التي تعمل أو توجه النشاطات باتجاهها أو هي النهايات التي تطمح النشاطات تحقيقها). ( 1 ) ..,

 كما تعرف أيضا بأنها (الأ

على بيتنا طبق

The objective of the research is to find the best method to estimate rice crop through out evaluating the applied methods of stratified random sampling .By using different sorts of sampling estimators, a comparison was held among the variances of the mean for simple random sampling, stratified random sampling(var()) and separate regression estimator. The results indicate that the separate regression estimator give best estimations. The approximate cum.f^4/5 method was used to determine the optimum stratum boundaries, new strata was put and then var () was calculated .In comparison with strata used nowadays in central statistical organization, the new strata led to obvious decrease in the variance. The stratified mean wa