SPECTRAL RATIO DISCRIMINANTS AND INFORMATION THEORY

DOI10.1111/j.1467-9892.1981.tb00313.xzbMath0509.62052OpenAlexW2126881873MaRDI QIDQ4747402

P. J. Laycock, G. R. Dargahi-Noubary

Publication date: 1981

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.1981.tb00313.x

zbMATH Keywords

frequency domainlikelihood ratiodiscriminationseismologyKullback- Leibler informationseismic recordsnon-stationary modelsdetection of nuclear explosionsinformation assessmentspectral ratioszero mean stationary Gaussian processes

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics (62P99) Inference from stochastic processes (62M99) Statistical aspects of information-theoretic topics (62B10)

Related Items (8)

Bootstrapping Frequency Domain Tests in Multivariate Time Series with an Application to Comparing Spectral Densities ⋮ Wavelet analysis of uniformly time-modulated processes ⋮ Discrimination of AR, MA and ARMA time series models ⋮ Discriminant analysis for non-gaussian vector stationary processes ⋮ A periodogram-based metric for time series classification ⋮ Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability ⋮ The Autoregressive metric for comparing time series models ⋮ Time series clustering and classification by the autoregressive metric

Cites Work

• Random differential equations in science and engineering
• Estimation for autoregressive moving average models in the time and frequency domains
• Large sample discrimination between two Gaussian processes with different spectra
• Classification into two Multivariate Normal Distributions with Different Covariance Matrices
• Linear Discriminant Functions for Stationary Time Series
• On the Distribution of Some Statistics Useful in the Analysis of Jointly Stationary Time Series
• Almost Periodic Variances
• An Application of Information Theory to Multivariate Analysis
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