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Probabilistic Forecasting Using Stochastic Diffusion Models, With Applications to Cohort Processes of Marriage and Fertility
2012
Demography
We study prediction and error propagation in the Hernes, Gompertz, and logistic stochastic diffusion models and use them to forecast demographic cohort processes. We develop a unified framework in which the models are linearized with respect to cohort age and predictions are derived from an underlying linear process. For prediction variance we develop a Monte Carlo estimator which can be used for a wide class of underlying linear processes. For the case of random walk with drift we develop an
doi:10.1007/s13524-012-0154-4
pmid:23104205
fatcat:mofqlvwobbf3lanf4vdanwy2gy