Article ID Journal Published Year Pages File Type
6369844 Journal of Theoretical Biology 2015 6 Pages PDF
Abstract
Recent work has highlighted the utility of nonparametric forecasting methods for predicting ecological time series (Perretti et al., 2013. Proc. Natl. Acad. Sci. U.S.A. 110, 5253-5257). However, one topic that has received considerably less attention is the quantification of uncertainty in nonparametric forecasts. This important topic was brought to the forefront in the recent work by Jabot (2014. J. Theor. Biol.). Here, we add to this emerging discussion by reviewing the available methods for quantifying forecast uncertainty in nonparametric models. We conclude with a demonstration of one such method using the simulation model of Jabot (2014. J. Theor. Biol.). We find that nonparametric forecast error is accurately estimated with as few as 10 observations in the time series.
Related Topics
Life Sciences Agricultural and Biological Sciences Agricultural and Biological Sciences (General)
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