文献类型：期刊文献

英文题名：Model and forecast for China's GDP based on combined ARIMA and linear regression model

作者：Xie, Jing[1]; Zhang, Wei[2]; Zhou, Tianyue[3]

机构：[1] Department of Mathematics, Shan Dong University, Shandong, China; [2] Department of Art and Media, East China University of Science and Technology, Shanghai, China; [3] Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, 93117, United States

年份：2022

卷号：12163

外文期刊名：Proceedings of SPIE - The International Society for Optical Engineering

收录：EI(收录号：20222412229003)

语种：英文

外文关键词：Linear regression

摘要：In this work, a combination of models is used to forecast the GDP of China and analyze the possible parameters that affect the GDP of China. The combined model includes linear regression model to establish relation between the GDP and possible significant parameters that affect the GDP and Autoregressive Integrated Moving Average model (ARIMA) to estimate and forecast those significant parameters. Consequently, these predicted parameters were brought in previous linear regression model, established a new model to forecast the GDP. After that, the new model was compared with the ARIMA model, then the probably more suitable model was used to predict the GDP of China in the future. The result of this work is that multiple linear regression model combined with the ARIMA model is more suitable in predicting the GDP of China. The significance of this work is that it states a new method which combined two models, and the new model is probably more suitable than the previous methods. As a result, other studies about GDP of China can consider this new method. ? COPYRIGHT SPIE.