تم إستعراض تقدير معلمتي التوزيع اللوجستي بإستعمال طريقة ذات مقدرات مضبوطة وهي طريقة العزوم، ومقارنتها بمقدرات تقريبية مأخوذة بالأساس من أسلوب طريقة (وايت) في التقدير بأعتبار التوزيع اللوجستي من التوزيعات الأحتمالية الأسية، وهي كل من طريقة المربعات الصغرى الأعتيادية، وطريقة أنحدار الحرف، وأقتراح تطبيق طريقة أنحدار الحرف المعدلة على هذا التوزيع. وتم أستحصال النتائج بالأستناد الى تجارب محاكاة لتلك الطر

Abstract

 The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .

The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation

This research deals with a shrinking method concerned with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

ملخـــص البحــــث

       كتاب(أدب الكاتب) كتابٌ موسوعي اعتنى صاحبه بعلوم اللغة العربية وغيرها، ويعدُّ من المصنفات المتقدمة الذي اعتنى بدراسة شروح المعاني، والذي يُعدُّ ثروة لفظية ومعنوية، إذ قام ابن قُتيبة بحشر الكثير من الألفاظ ومعانيها فيه، وهو من دواوين العرب الأربعة التي ذكرها ابن خلدون(ت28 رمضان 808 هـ الموافق 19 مارس 1406م) قائلًا:(( و سمعنا من شيوخنا في مجالس التعليم أن أصول

يعد الهواء من الضروريات لعيش الانسان وكلما كان الهواء نقياً كلما كانت صحة الانسان جيدة، وفي الآونة الاخيرة اصبح الهواء يتأثر بالملوثات وهنالك عدة متغيرات تؤثر في نقاوة الهواء واصبح الهواء يؤثر على صحة الانسان لما يحمله من ملوثات توثر على جسم الانسان وصحته. ولمعرفة مدى تلوث الهواء في كل مناطق الارض تم بناء مؤشر لمعرف تلوث الهواء بالاعتماد على عدة متغيرات يسمى بمعامل تأثير الهواء. ولبيان اكثر المتغيرات تأ

Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.