Forecasting mortality rate by multivariate singular spectrum analysis
Rahim Mahmoudvand, Dimitrios G. Konstantinides, Paulo Canas Rodrigues
Abstract
Rahim Mahmoudvand, Dimitrios G. Konstantinides, Paulo Canas Rodrigues
Abstract
In this paper, we investigate the possibility of using multivariate singular spectrum analysis (SSA), a nonparametric technique in the field of time series analysis, for mortality forecasting. We consider a real data application with 9 European countries: Belgium, Denmark, Finland, France, Italy, Netherlands, Norway, Sweden, and Switzerland, over a period 1900 to 2009, and a simulation study based on the data set. The results show the superiority of multivariate SSA in comparison with the univariate SSA, in terms of forecasting accuracy.
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In this paper, we investigate the possibility of using multivariate singular spectrum analysis (SSA), a nonparametric technique in the field of time series analysis, for mortality forecasting. We consider a real data application with 9 European countries: Belgium, Denmark, Finland, France, Italy, Netherlands, Norway, Sweden, and Switzerland, over a period 1900 to 2009, and a simulation study based on the data set. The results show the superiority of multivariate SSA in comparison with the univariate SSA, in terms of forecasting accuracy.
Key concepts: Multivariate statistics, Singular spectrum analysis, Univariate, Multivariate analysis, Econometrics, Nonparametric statistics, Statistics, Mathematics