Operation forecast and influencing factors analysis of pension market based on grey correlation analysis

Abstract

Aiming at the operation problem of pension market, this paper establishes multiple linear model, auto-regressive integral moving average model and other prediction models through data analysis of nursing service beds, multiple linear regression and grey correlation analysis, etc. programming software such as SPSS and MATLAB are used to make the prediction model of pension market, and the grey correlation degree is used to discuss the influence variables Through the research of population factor and economic factor, it is concluded that the most important factor affecting the number of nursing beds is per capita GDP.