Prediction in the Worst Case
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Statistics Papers
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comparing forecasts
worst-case behavior
mean square error
Statistics and Probability
worst-case behavior
mean square error
Statistics and Probability
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Foster, Dean P
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Abstract
A predictor is a method of estimating the probability of future events over an infinite data sequence. One predictor is as strong as another if for all data sequences the former has at most the mean square error (MSE) of the latter. Given any countable set D of predictors, we explicitly construct a predictor S that is at least as strong as every element of D. Finite sample bounds are also given which hold uniformly on the space of all possible data.
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1991
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The Annals of Statistics
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At the time of publication, author Dean Foster was affiliated with the University of Chicago. Currently, he is a faculty member at the Statistics Department at the University of Pennsylvania.