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Sampling distributions of post-sample forecasting errors. (English) Zbl 0707.62193

Summary: Forecasting errors fall in two clearly different categories: (a) the residual errors from fitting a model to the available data and (b) the post-sample forecasting errors. The emphasis of statistical theory and forecasting methodology has been on model fitting errors, even though the greatest concern in applied work should be with post-sample errors. The purpose of this paper is to investigate empirically sampling distributions of post-sample forecasting errors. The characteristics of such distributions are studied and compared with characteristics of distributions of model fitting errors. The discrepancies between characteristics of model fitting and post-sample errors are quite large and somewhat variable.

MSC:

62M20 Inference from stochastic processes and prediction
62F10 Point estimation
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