The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also showed that the estimated missing value was larger than the original value when the missing value situated either in the middle or at the end of the series while the sign was negative or the estimated value was less than the original value when the missing value situated in the beginning of the time series. All of that would affect the estimated values outside the time series data according to estimated value of missing value. The research recommended to work on the analysis of the effect of missing more than one value and also when the missing is in the dependent variable only and in both dependent and independent variables.
This study aims to discuss the projects of poultry in Wasit province in 2013 and geographical distribution according to the type and contrast on the level of administrative units representing Districts and The reasons for this discrepancy, as well as knowledge of the factors affecting the distribution by the analysis and reasoning and description This study divided to the four themes, The first of the statement of nutritional importance and economic Poultry focused on the importance of various poultry products, The second one shows the relative position of the province of Wasit between the provinces of Iraq in poultry and production of eggs and meat farming projects, and then followed by the third one (theme) as it ensures the geographic
... Show MoreThe 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
... Show MoreAbstract
The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable. &nb
... Show MoreAttitude is an important subject that has attracted researchers and thinkers in organizational theory and organizational behavior because of its great importance in various field studies. Field evidence suggests that individuals in their daily lives or careers respond to specific events through a set of internal tendencies Internal tendencies are negative or positive and systematic. These trends tend to be invisible, not limited to certain boundaries, and involve a significant number of individuals within organizations or society.
The research aims to identify the impact of trends in the ethics of public service workers for individuals, through a sample of (72) doctors and (60) administrative staff
... Show MoreIn this research, the methods of Kernel estimator (nonparametric density estimator) were relied upon in estimating the two-response logistic regression, where the comparison was used between the method of Nadaraya-Watson and the method of Local Scoring algorithm, and optimal Smoothing parameter λ was estimated by the methods of Cross-validation and generalized Cross-validation, bandwidth optimal λ has a clear effect in the estimation process. It also has a key role in smoothing the curve as it approaches the real curve, and the goal of using the Kernel estimator is to modify the observations so that we can obtain estimators with characteristics close to the properties of real parameters, and based on medical data for patients with chro
... Show MoreResearchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
... Show MoreThe research dealt with the case stock repurchase policy of Emaar Real Estate Company one of listed companies in Dubai Stock exchange. The research has launched from the cognitive dimensions of repurchasing policy which took great concern in the literatures of financial management, and also this policy became as substitute for distributing the monitory profit in the last three decades in the international financial markets, but it did not get any importance in the Arab Markets such as that of the Arab Gulf in addition to the Iraqi Stock Exchange.
The research summarized a set of conclusions, the most important one was the consistence of analysis result with the test of the major two hypotheses (The first
... Show MoreUse of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)
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
... Show MoreIn this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.