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Titolo:
The spectral envelope and its applications
Autore:
Stoffer, DS; Tyler, DE; Wendt, DA;
Indirizzi:
Univ Pittsburgh, Dept Stat, Cathedral Learning 2630, Pittsburgh, PA 15260 USA Univ Pittsburgh Pittsburgh PA USA 15260 ng 2630, Pittsburgh, PA 15260 USA Rutgers State Univ, Dept Stat, Hill Ctr, New Brunswick, NJ 08903 USA Rutgers State Univ New Brunswick NJ USA 08903 New Brunswick, NJ 08903 USA
Titolo Testata:
STATISTICAL SCIENCE
fascicolo: 3, volume: 15, anno: 2000,
pagine: 224 - 253
SICI:
0883-4237(200008)15:3<224:TSEAIA>2.0.ZU;2-#
Fonte:
ISI
Lingua:
ENG
Soggetto:
CATEGORICAL TIME-SERIES; OPTIMAL TRANSFORMATIONS; WAVELET SHRINKAGE; PERIODICITY; IMAGE; HYDROPHOBICITY; DINUCLEOTIDES; REGRESSION; SEQUENCES; FIELDS;
Keywords:
spectral envelope; optimal scaling; Fourier analysis; latent roots and vectors; principal components; canonical correlation; signal detection; optimal transformations; coherency; random fields; categorical-valued time series; EEG sleep states; DNA; US GNP growth rate; residual analysis; long range dependence; matching sequences; functional magnetic resonance imaging (fMRI); pain perception; textures; image retrival;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
51
Recensione:
Indirizzi per estratti:
Indirizzo: Stoffer, DS Univ Pittsburgh, Dept Stat, Cathedral Learning 2630, Pittsburgh, PA 15260 USA Univ Pittsburgh Pittsburgh PA USA 15260 tsburgh, PA 15260 USA
Citazione:
D.S. Stoffer et al., "The spectral envelope and its applications", STAT SCI, 15(3), 2000, pp. 224-253

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 oftextures.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 05/04/20 alle ore 23:10:16