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comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
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 The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method  local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned method using simulation at sample sizes (n = 100,150,200) as it found that the estimated proposed( C.S.S-L.S.I) is the best among the studied capabilities.

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Publication Date
Sat Sep 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Ordinary Method and Robust Method to estimate the Parameters of the Univariate Mixed Model with Low Order
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A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.

 

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation
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In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Planning the Production of the Electrical Distribution Converter (400KV/11) Using Time Series Methods and Goal Programming in the Fuzzy Environment
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This Paper aims to plan the production of the electrical distribution converter (400 KV/11) for one month at Diyala Public Company and with more than one goal for the decision-maker in a fuzzy environment. The fuzzy demand was forecasting using the fuzzy time series model. The fuzzy lead time for raw materials involved in the production of the electrical distribution converter (400 KV/11) was addressed using the fuzzy inference matrix through the application of the matrix in Matlab, and since the decision-maker has more than one goal, so a mathematical model of goal programming was create, which aims to achieve two goals, the first is to reduce the total production costs of the electrical distribution converter (400 KV/11) and th

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compare between simex and Quassi-likelihood methods in estimation of regression function in the presence of measurement error
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       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index
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     As is  known that the consumer price index (CPI) is one of the most important  price indices because of its direct effect on the welfare of the individual and his living.

       We have been address the problem of Strongly  seasonal  commodities in calculating  (CPI) and identifying some of the solution.

   We have  used an actual data  for a set of commodities (including strongly seasonal commodities) to calculate the index price by using (Annual Basket With Carry Forward Prices method) . Although this method can be successfully used in the context of seasonal&nbs

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Tree regression (TR), and Negative binomial regression (NBR) by Using Simulation.
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            In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
A comparison Some of Methods for Estimating Survival Function for Truncated Exponential Distribution
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Exponential distribution is one of most common distributions in studies and scientific researches with wide application in the fields of reliability, engineering and in analyzing survival function therefore the researcher has carried on extended studies in the characteristics of this distribution.

In this research, estimation of survival function for truncated exponential distribution in the maximum likelihood  methods and Bayes first and second method, least square method and Jackknife dependent in the first place on the maximum likelihood method, then on Bayes first method then comparing then using simulation, thus to accomplish this task, different size samples have been adopted by the searcher us

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Publication Date
Wed Feb 10 2016
Journal Name
ألمؤتمر الدولي العلمي الخامس للاحصائيين العرب/ القاهرة
Proposition of Modified Genetic Algorithm to Estimate Additive Model by using Simulation
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Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Partial Least Square Regression(PLSR) and Tree Regression by Using Simulation(RT).
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This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The use of the genetic algorithm to estimate the parameters function of the hypoexponential distribution by simulation
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In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

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