Abstract
The concept of the spectral envelope was recently introduced as a statistical basis for the frequency domain analysis and scaling of qualitative-valued time series. In the process of developing the spectral envelope methodology, many other interesting extensions became evident. In this article we explain the basic concept and give numerous examples of the usefulness of the technology. These examples include analyses of DNA sequences, finding optimal transformations for the analysis of real-valued time series, residual analysis, detecting common signals in many time series, and the analysis of textures. © 2000 Institute of Mathematical Statistics.
Author supplied keywords
- Canonical correlation
- Categorical-valued time series
- Coherency
- DNA
- EEG sleep states
- Fourier analysis
- Functional magnetic resonance imaging (fMRI)
- Image retrival
- Latent roots and vectors
- Long range dependence
- Matching sequences
- Optimal scaling
- Optimal transformations
- Pain perception
- Principal components
- Random fields
- Residual analysis
- Signal detection
- Spectral envelope
- Textures
- US GNP growth rate
Cite
CITATION STYLE
Stoffer, D. S., Tyler, D. E., & Wendt, D. A. (2000). The spectral envelope and its applications. Statistical Science, 15(3), 224–253. https://doi.org/10.1214/ss/1009212816
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