Journal of the American Statistical Association volume 80, issue 392, P1026-1031 1985 DOI: 10.1080/01621459.1985.10478220 View full text
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Robert A. Stine

Abstract: Bootstrap prediction intervals provide a nonparametric measure of the probable error of forecasts from a standard linear regression model. These intervals approximate the nominal probability content in small samples without requiring specific assumptions about the sampling distribution. Empirical measures of the prediction error rate motivate the choice of these intervals, which are calculated by an application of the bootstrap. The intervals are contrasted to other nonparametric procedures in several Monte C…

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