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Calculating the Distribution of the Serial Correlation Estimator by Saddlepoint Integration

Published online by Cambridge University Press:  11 February 2009

Carl W. Helstrom
Affiliation:
University of California, San Diego

Abstract

The efficient method of numerical saddlepoint integration is described and applied to calculating the probability distribution of the maximum likelihood and Yule-Walker estimators of the correlation coefficient a of a first-order autoregressive normal time series with initial value either zero or nonzero when a finite number n of data are at hand. Stationary time series of the same type are also treated. Significance points are computed in a number of examples to show how, as n increases, the finite-sample distributions approach the asymptotic distributions that have appeared in the literature.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 1996

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