标题:
组合时间序列模型在江西省农业总产值预测中的应用Application of the Combination Time Series Model in Forecasting the Gross Agriculture Output of Jiangxi Province
作者:
田小发
关键字:
GM(1, 1)模型, 指数模型, 混合时间序列模型, 组合预测模型, 农业总产值GM(1, 1) Model, Exponent Model, Mixed-Time Series Model, Combination Prediction Model, Gross Agriculture Output
期刊名称:
《Statistics and Application》, Vol.4 No.4, 2015-12-16
摘要:
本文选取1979~2014年江西省农业总产值，利用江西省农业总产值1979~2009年数据分别建立GM(1,1)模型、指数曲线模型和混合时间序列模型，并用2010~2012年的数据进行模型检验，然后在三个模型的基础上，建立组合时间序列模型对江西省最近几年的农业总产值进行预测。通过组合模型预测与单个模型预测结果比较表明，组合预测模型所得结果误差优于三个模型的分别预测,在时间序列数据的预测中更有优势。预测2015年江西省农业总产值为3385.07亿元。但江西省2015年的目标是农业总产值达到3800亿元，与目标差距较大，因此应加大对农业的投入。
This article selects Jiangxi province’s 1979-2014 agricultural output, using the Jiangxi agricul-tural gross output value of 1979-2009 data, respectively to set up the GM(1,1) model, the expo-nential curve model and mixed time series model. The data from 2010-2012 were used for the model test, and then on the basis of the three models, the combination of time series model was established to predict agricultural output of the Jiangxi province in recent years. Combined model prediction with a single model predicted results comparison shows that the results error of com-bination forecasting model is superior to the three model predictions respectively, and has more advantages in prediction of time series data. The prediction of 2015 Jiangxi province’s agricultural output was 3385.07 billion Yuan, but it totally reached 3800 billion Yuan in 2015. For the wide gap with the expection, we should increase investment in agriculture.