%0 Journal Article
%T 时间序列分析在山东省GDP分析预测中的应用<br>Application of Time Series Analysis in GDP Analysis and Forecasting in Shandong Province
%A 刘子瑜
%A 吴清
%J Advances in Applied Mathematics
%P 5079-5085
%@ 2324-8009
%D 2022
%I Hans Publishing
%R 10.12677/AAM.2022.118533
%X GDP可以反映一个地区经济的发展变化情况，本文利用山东省1978~2020年生产总值的数据，通过图检验和假设检验两种方式确定平稳性，通过二阶差分转换为平稳序列，拟合出ARIMA(1,2,0)模型，ARIMA被广泛应用于单变量时间序列数据预测，便利性十分突出，仅使用内生变量就足够达到预测效果。借助模型预测未来几年山东省GDP仍将处于快速发展的水平，对未来山东省的发展布局起到了一定的现实意义。<br />
GDP can reflect the development and change of a region’s economy. In this paper, we use the data of GDP of Shandong Province from 1978 to 2020 to determine the smoothness by both graph test and hypothesis test, and fit the ARIMA(1,2,0) model by converting it into a smooth series through sec-ond-order difference. ARIMA is widely used for univariate time series data forecasting, the conven-ience is outstanding and the use of endogenous variables alone is sufficient to achieve the forecast-ing effect. With the help of the model, it is predicted that the GDP of Shandong Province will remain at a rapid level in the coming years, which plays a realistic role in the future layout of Shandong Province.
%K 时间序列模型，山东GDP，预测<br>Time Series Models
%K Shandong GDP
%K Forecast
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=54358