Predictions the GDP of Iraq by using Grey –Linear Regression Combined Model

Shamsur Rahim, S. O. Salih, A. O. Hamdin, Hindreen Abdullah Taher
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引用次数: 1

Abstract

: Gross Domestic Product (GDP) is the total pecuniary or mart value of all final commodity and services that are produced within country's borders in a given time. We choose GDP to predict in Iraq since 2000 to 2018.The state and governments rely on GDP to help shape policy or decide how much public spending is affordable. Combining grey regression is a modern statistical technique of modeling, using this type of model is related to its highly accuracy therefor, in this study we used combined grey regression model to predict the gross domestic production of Iraq because it gives less Mse than grey or regression models alone which is equal to 1.3165 and estimated parameter of grey C 1 , regression C 2 are equals to (2.9 and 0.205) respectively and the intercept C 3 is equal to 1.8569 the outcome showed that the new model could attain preferable predicting result contrasted with different predicting methods.
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运用灰色-线性回归组合模型预测伊拉克GDP
国内生产总值(GDP)是一个国家在一定时间内生产的所有最终商品和服务的货币总价值或市场价值。我们选择从2000年到2018年的伊拉克GDP来预测。国家和政府依靠GDP来帮助制定政策或决定多少公共支出是可以承受的。结合灰色回归是一种现代统计建模技术,使用这种类型的模型与它的高准确性有关,因此,在本研究中,我们使用结合灰色回归模型来预测伊拉克的国内生产总值,因为它给出的Mse小于单独的灰色或回归模型,它等于1.3165,估计参数为灰色c1。回归c2分别等于(2.9和0.205),截距c3等于1.8569,结果表明,与不同的预测方法相比,新模型能获得较好的预测结果。
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