Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/24300
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dc.contributor.authorM. Sorkatti, Rabab-
dc.contributor.authorAbdel-lateef, Afra H.-
dc.contributor.authorKhider, Khalid R.-
dc.date.accessioned2019-12-30T11:05:51Z-
dc.date.available2019-12-30T11:05:51Z-
dc.date.issued2019-12-01-
dc.identifier.citation1. M. Sorkatti, Rabab. Determining the Best Method for Estimating in Sudan during the period (1982-2008)/ Rabab M. Sorkatti, Dr. Afra H. Abdel-lateef, Dr.Khalid R. Khider.- vol 20 , no 2.- articleen_US
dc.identifier.issn1858-6716-
dc.identifier.urihttp://repository.sustech.edu/handle/123456789/24300-
dc.description.abstractThe paper aimed at determining the Best Method for Estimating in Sudan during the period (1982-2008).The paper used the descriptive – analytic approach (summarizing and describing a body of data and testing the significancy of the parameters) for the data was given by Central Bureau of Statistics (CBS) /Sudan also it use the data from reports and publications from other relevant sides like Central Bank of Sudan and Sudan household survey 2006. for estimating GDP by Prediction Residual Error Sum of Squares (PRESS) method after excluding the outliers values, the prediction sum of squares is a useful statistic for comparing different models. Moreover, the findings showed that PRESS method model bring estimated value for DGP more relevant to the actual value than traditional method which indicate that PRESS method is the best for estimating the future value. Based on these findings the paper calls for more application of the criteria for selection the best model.en_US
dc.description.sponsorshipSudan university of science and technologyen_US
dc.language.isoen_USen_US
dc.publisherSudan University of Science and Technologyen_US
dc.subjectregressionen_US
dc.subjectoutlieren_US
dc.subjectP.R.E.S.Sen_US
dc.subjectG.D.Pen_US
dc.titleDetermining the Best Method for Estimating in Sudan during the period (1982-2008)en_US
dc.typeArticleen_US
Appears in Collections:Volume 20 No. 2

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