Biometrika Advance Access originally published online on January 30, 2009
Biometrika 2009 96(1):119-132; doi:10.1093/biomet/asn071
Articles |
Tapered empirical likelihood for time series data in time and frequency domains
Department of Statistics, Iowa State University, Ames, Iowa 50011, U.S.A. dnordman{at}iastate.edu
Received for publication 1 May 2007. Revision received 1 August 2008.
We investigate data tapering in two formulations of empirical likelihood for time series. One empirical likelihood is formed from tapered data blocks in the time domain and a second is based on the tapered periodogram in the frequency domain. Limiting distributions are provided for both empirical likelihood versions under tapering. Theoretical and simulation evidence indicates that a data taper improves the coverage accuracy of empirical likelihood confidence intervals for time series parameters, such as means and correlations.
Key Words: Block bootstrap Confidence interval Empirical likelihood Periodogram Tapering Variance estimation
References
-
Bravo F. Blockwise empirical entropy tests for time series regressions. J. Time Ser. Anal. (2005) 26:185–210.[CrossRef]
Brillinger D. R. Time Series: Data Analysis and Theory. (1981) San Francisco, CA: Holden-Day.
Dahlhaus R. Spectral analysis with tapered data. J. Time Ser. Anal. (1983) 4:163–75.[CrossRef]
Dahlhaus R. Asymptotic normality of spectral estimates. J. Mult. Anal. (1985) 16:412–31.[CrossRef]
Dahlhaus R., Janas D. A frequency-domain bootstrap for ratio statistics in time series analysis. Ann. Statist. (1996) 24:1934–63.[CrossRef]
Doukhan P. Mixing: Properties and Examples (1994) 85. New York: Springer. Lecture Notes in Statistics.
Dzhaparidze K. Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series. (1986) New York: Springer.
Götze F., Künsch H. Second-order correctness of the blockwise bootstrap for stationary observations. Ann. Statist. (1996) 24:1914–33.[CrossRef]
Hall P. The Bootstrap and Edgeworth Expansion (1992) New York: Springer.
Hall P., La Scala B. Methodology and algorithms of empirical likelihood. Int. Statist. Rev. (1990) 58:109–27.
Ibragimov I. A., Linnik Y. V. Independent and Stationary Sequences of Random Variables. (1971) Groningen, the Netherlands: Wolters-Noordhoff.
Janas D. Edgeworth expansions for spectral mean estimates with application to Whittle estimates. Ann. Inst. Statist. Math. (1993) 46:667–82.[CrossRef]
Kitamura Y. Empirical likelihood methods with weakly dependent processes. Ann. Statist. (1997) 25:2084–102.[CrossRef]
Künsch H. R. The jackknife and bootstrap for general stationary observations. Ann. Statist. (1989) 17:1217–61.[CrossRef]
Lahiri S. N. Resampling Methods for Dependent Data (2003) New York: Springer.
Lahiri S. N. Asymptotic expansions for sums of block-variables under weak dependence. Ann. Statist. (2007) 35:1324–50.[CrossRef]
Lin L., Zhang R. Blockwise empirical Euclidean likelihood for weakly dependent processes. Statist. Prob. Lett. (2001) 53:143–52.[CrossRef]
Monti A. C. Empirical likelihood confidence regions in time series models. Biometrika (1997) 84:395–405.
Nordman D. J., Lahiri S. N. A frequency-domain empirical likelihood for short- and long-range dependence. Ann. Statist. (2006) 34:3019–50.[CrossRef]
Nordman D. J., Sibbertsen P., Lahiri S. N. Empirical likelihood for the mean under long-range dependence. J. Time Ser. Anal. (2007) 28:576–99.[CrossRef]
Owen A. B. Empirical likelihood confidence regions. Ann. Statist. (1990) 18:90–120.[CrossRef]
Paparoditis E., Politis D. N. Tapered block bootstrap. Biometrika (2001) 88:1105–19.
Paparoditis E., Politis D. N. The tapered block bootstrap for general statistics from stationary sequences. Economet. J. (2002) 5:131–48.[CrossRef]
Politis D. N., Romano J. P. Bias-corrected nonparametric spectral estimation. J. Time Ser. Anal. (1995) 16:67–103.[CrossRef]
Politis D. N., White H. Automatic block-length selection for the dependent bootstrap. Economet. Rev. (2004) 23:53–70.[CrossRef]
Politis D. N., Romano J. P., Wolf M. Subsampling. (1999) New York: Springer.
Tikhomirov A. N. On the rate of convergence in the central limit theorem for weakly dependent random variables. Prob. Theory Appl. (1980) 25:800–18.
Welch P. D. The use of the fast Fourier transform for estimation of spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust. (1967) 15:70–3.[CrossRef]
Zhang J. Empirical likelihood for NA series. Statist. Prob. Lett. (2006) 76:153–60.
| ||||||||||||||||||||||||||||||||||||||||||||||||