Academic Journal of Humanities & Social Sciences, 2021, 4(6); doi: 10.25236/AJHSS.2021.040616.
Yingjian Rui1, Yueran Lu1, Zhongwen Huang2, Linging Han3
1School of Finance, Anhui University of Finance and Economics, Bengbu, Anhui 233000, China
2Navigation College, Dalian Maritime University, Dalian, Liaoning 116000, China
3School of Art, Anhui University of Finance and Economics, Bengbu, Anhui 233000, China
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.
Nursing bed, multiple linear regression, grey correlation analysis, GDP per capita, forecast, MATLAB
Yingjian Rui, Yueran Lu, Zhongwen Huang, Linging Han. Operation forecast and influencing factors analysis of pension market based on grey correlation analysis. Academic Journal of Humanities & Social Sciences (2021) Vol. 4, Issue 6: 99-108. https://doi.org/10.25236/AJHSS.2021.040616.
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