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Philip Hans Franses.Time Series Models for Business and Economic Forecasting[M].Beijing: Chinese People’s University Press.2002.

has been cited by the following article:

• TITLE: Based on ODE and ARIMA Modeling for the population of China

  AUTHORS: Xiaohua Hu, Min Yu

  KEYWORDS: Natural Asset; Financial Value; Neural Network

  JOURNAL NAME: Technology and Investment, Vol.4 No.1B, January 17, 2013

  ABSTRACT: The economic data usually can be also composed into a deterministic part and a random part. We establish ordinary differential equations (ODE) model for the deterministic part from a purely mathematical point of view, via the prin-ciple of integral and difference, establishing ()ARIMApdq,, model for the random part, to combine the two estab-lished models to predict and control the original series, then we apply the method to study the population of China from 1978 to 2007, establishing the corresponding mathematical model, to obtain the forecast data of the population of China in 2008(1.3879503 billion), finally we make further stability analysis.