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- Stoffer, David S., et al. Show all 5 Authors
- Journal of the American Statistical Association 2017 v.112 no.520 pp. 1405-1416
- Markov chain; Monte Carlo method; algorithms; automation; elderly; geometry; medicine; models; sleep; spectral analysis; time series analysis
- ... This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to noninvasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified ...
- Stoffer, David S., et al. Show all 3 Authors
- Journal of the American Statistical Association 2012 v.107 no.500 pp. 1575-1589
- El Nino; Markov chain; electroencephalography; models; time series analysis
- ... We propose a method for analyzing possibly nonstationary time series by adaptively dividing the time series into an unknown but finite number of segments and estimating the corresponding local spectra by smoothing splines. The model is formulated in a Bayesian framework, and the estimation relies on reversible jump Markov chain Monte Carlo (RJMCMC) methods. For a given segmentation of the time ser ...