%0 Journal Article
%T 基于ARIMA模型的江苏省GDP预测分析<br>GDP Forecast Analysis of Jiangsu Province Based on ARIMA Model
%A 张媛媛
%J Statistics and Applications
%P 367-374
%@ 2325-226X
%D 2022
%I Hans Publishing
%R 10.12677/SA.2022.112039
%X 本文基于1975~2020年江苏省GDP数据，运用R软件对1975~2015年的时间序列数据建立模型，再通过比较AIC信息准则值以及观察自相关以及偏自相关图像，确定最优模型：疏系数模型。之后运用对比得到的最优模型对于江苏省2016~2020年的GDP数值进行预测分析，并将预测值与真实值进行对比，结果显示利用该模型进行预测的误差较小，模型精度较高的结论。进而说明疏系数模型对于江苏省GDP预测工作的准确性。<br />
Based on the GDP data of Jiangsu Province from 1975 to 2020, R software was used to build a model for the time series data from 1975 to 2015, and then the optimal model was determined by comparing AIC information criterion values and observing autocorrelation and partial autocorrelation images: sparse coefficient model. After that, the optimal model obtained by comparison is used to forecast and analyze the GDP value of Jiangsu Province from 2016 to 2020, and the predicted value is compared with the real value. The results show that the prediction error of using this model is small, and the model has high accuracy. Then it shows the accuracy of the thinning coefficient model for GDP forecasting in Jiangsu Province.
%K ARIMA模型，江苏省GDP预测，时间序列，疏系数<br>ARIMA Model
%K GDP Forecast of Jiangsu Province
%K Time Series
%K Sparse Coefficient
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=50460