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September, 1987 Model-Free One-Step-Ahead Prediction Intervals: Asymptotic Theory and Small Sample Simulations
Sinsup Cho, Robert B. Miller
Ann. Statist. 15(3): 1064-1078 (September, 1987). DOI: 10.1214/aos/1176350493

Abstract

We show that the empirical quantile process from an ARMA$(1, q)$ process which is strongly mixing $\Delta_s$, and is either Gaussian or double exponential, converges to a Gaussian process. This result is used to derive model-free one-step-ahead prediction intervals for such processes. Simulations demonstrate where the asymptotic theory can and cannot be applied to small samples.

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Sinsup Cho. Robert B. Miller. "Model-Free One-Step-Ahead Prediction Intervals: Asymptotic Theory and Small Sample Simulations." Ann. Statist. 15 (3) 1064 - 1078, September, 1987. https://doi.org/10.1214/aos/1176350493

Information

Published: September, 1987
First available in Project Euclid: 12 April 2007

zbMATH: 0627.62095
MathSciNet: MR902246
Digital Object Identifier: 10.1214/aos/1176350493

Subjects:
Primary: 62G30
Secondary: 62M20

Rights: Copyright © 1987 Institute of Mathematical Statistics

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Vol.15 • No. 3 • September, 1987
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