Articles |
Confidence intervals for spectral mean and ratio statistics
Department of Statistics, University of Illinois at Urbana-Champaign, 725 South Wright Street, Champaign, Illinois 61820, U.S.A. xshao{at}uiuc.edu
Received for publication 1 January 2008.
Revision received 1 June 2008.
| Abstract |
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We propose a new method, to construct confidence intervals for spectral mean and related ratio statistics of a stationary process, that avoids direct estimation of their asymptotic variances. By introducing a bandwidth, a self-normalization procedure is adopted and the distribution of the new statistic is asymptotically nuisance-parameter free. The bandwidth is chosen using information criteria and a moving average sieve approximation. Through a simulation study, we demonstrate good finite sample performance of our method when the sample size is moderate, while a comparison with an empirical likelihood-based method for ratio statistics is made, confirming a wider applicability of our method.
Key Words: Autocorrelation Cumulant Ratio statistic Spectral density Spectral distribution function