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 research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at

Abstract

 The issue of inequality in distribution of income and / or consumption expenditure is related to economic welfare because there is an inverse relationship between the economic welfare on the one hand, and the degree of inequality, on the other hand. Despite the fact that inequality is considered as normal phenomenon in every society, but if it exceeded certain limits it will lead to undesirable economic, social and political consequences. Therefore, the availability of indicators about inequality is a necessary tool for planning and evaluation of economic development programs. So, current study is aiming at measuring and analyzing the degree of inequality in distribution of consumpti

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

A field Experiment was carried out in Baghdad for the purpose of compare five horticulture machines during used two types of fuel deffirance in octane number, normal and super fuel which produced in Iraqi and measuring the vibrations transmitted of the three axes are longitudinal X , lateral Y and vertical Z from handlebar in (Mowers) to the operator which walks behind the mower, and the determine of the productivity practical of cutting, productivity passing and fuel consumption. Experiment Factorial used with two factors, The first factor was Five Mowers vary in width , types, weight and company manufacturer, The Second factor was the types of fuel used internal combination engine horticulture mowers were Normal fuel with Octane Number 82

      This research aims at making a comparative survey between the dry season in (2017-2018) and the wet season (2018-2019) in Iraq concerning the variation of rainfall and pressure systems responsible for such a difference. In this paper, seven climatological stations have been selected: Mosul, Kirkuk, Khanaqin, Baghdad, Rutba, Diwaniyah and Basra. Results have shown that the first category of rainfall of the two seasons has recorded a higher number of rainy days in comparison with the second and third categories with a total of 274 day in a dry season and 403 day of a wet season. Further, the total amount of the annual continuous rain is higher than the total of thunderstorms in a dry season as well as in the

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted