Prediction Intervals for Stationary Time Series Using the Sieve Bootstrap Method

by Adam Zagdanski .

Abstract: We consider the problem of constructing prediction intervals for future observations of stationary time series. Our approach relies on the sieve bootstrap procedure. A more traditional Gaussian strategy is also presented. Accuracy of the proposed methods is verified via numerical comparison including both Gaussian and non-Gaussian data.

Key Words: Prediction Interval, Bootstrap, Method of Sieves

Adam Zagdanski,

Editor: Wei-Min Huang ,

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