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Spectral

Email questions about the code to pfc <AT> stat.osu.edu

A R package for carrying out the spectral analysis of univariate time series. The package is contained in the spectral folder. Different versions of the R package are in the releases folder.

Now includes R functions for carrying out spectral-based tests of periodicity. Extra code used in Wei and Craigmile (2010) are contained in the folder spectral_tests_of_periodicity. Code testing some of the function in the R package are in tests.

Supported by the National Science Foundation under award number DMS-0604963 and DMS-0906864.

Installation

Please make sure you have a C and Fortran compiler installed for your version of R. Then, after installing the devtools R package, you can install this R package using

devtools::install_github("petercraigmile/spectral/spectral")

After installation, type library(spectral) to use the R library.

Issues:

The following functions used for spectral-based tests of periodicity are undocumented.

 Deni.Wald.crit Deni.Wald.setup Deni.Wald.stat Thomson.test
 global.Ftest hcrits hearing.stat hearing.stat.crit
 hearing.stat.pvalue local.Ftest local.Ftest.Satterthwaite

The documentation for Thomson.stat is incorrect.

References:

D. R. Brillinger. Time Series: Data Analysis and Theory. Holt, New York, NY, 1981.

D. Percival and A. Walden. Spectral Analysis for Univariate Time Series. Cambridge University Press, Cambridge, 2020.

M. B. Priestley. Spectral Analysis and Time Series. (Vol. 1): Univariate Series. Academic Press, London, UK, 1981.

A. T. Walden, E. J. McCoy and D. B. Percival (1995), The Effective Bandwidth of a Multitaper Spectral Estimator, Biometrika, 82, 201-14

L. Wei and P. F. Craigmile (2010). Global and local spectral-based tests for periodicities. Biometrika, 97, 223-230.

P. F. Craigmile, and W. M. King (2004). Periodogram based tests for distortion products otoacoustic emission. The Journal of the Acoustical Society of America, 116, 442-451

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R routines for carrying out the univariate spectral analysis of time series

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