Confidence intervals for spectral mean and ratio statistics

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)107-117
Number of pages11
Issue number1
StatePublished - Mar 2009


  • Autocorrelation
  • Cumulant
  • Ratio statistic
  • Spectral density
  • Spectral distribution function

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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