View source: R/spec-estimation.R
SpecMTM | R Documentation |
This is a wrapper for the spec.mtm
function from
package multitaper, which sets convenient defaults for the spectral estimate
and makes the degrees of freedom accessible as a direct list element of the
output.
SpecMTM(
timeSeries,
k = 3,
nw = 2,
nFFT = "default",
centre = c("Slepian"),
dpssIN = NULL,
returnZeroFreq = FALSE,
Ftest = FALSE,
jackknife = FALSE,
jkCIProb = 0.95,
maxAdaptiveIterations = 100,
plot = FALSE,
na.action = stats::na.fail,
returnInternals = FALSE,
detrend = TRUE,
bPad = FALSE,
...
)
timeSeries |
A time series of equally spaced data, this can be created by the ts() function where deltat is specified. |
k |
k a positive integer, the number of tapers, often 2*nw. |
nw |
nw a positive double precision number, the time-bandwidth parameter. |
nFFT |
This function pads the data before computing the fft. nFFT indicates the total length of the data after padding. |
centre |
The time series is centred using one of three methods: expansion onto discrete prolate spheroidal sequences ('Slepian'), arithmetic mean ('arithMean'), trimmed mean ('trimMean'), or not at all ('none'). |
dpssIN |
Allows the user to enter a dpss object which has already been created. This can save computation time when Slepians with the same bandwidth parameter and same number of tapers are used repeatedly. |
returnZeroFreq |
Boolean variable indicating if the zeroth frequency (DC component) should be returned for all applicable arrays. |
Ftest |
Boolean variable indicating if the Ftest result should be computed and returned. |
jackknife |
Boolean variable indicating if jackknifed confidence intervals should be computed and returned. |
jkCIProb |
Decimal value indicating the jackknife probability for calculating jackknife confidence intervals. The default returns a 95% confidence interval. |
maxAdaptiveIterations |
Maximum number of iterations in the adaptive multitaper calculation. Generally convergence is quick, and should require less than 100 iterations. |
plot |
Boolean variable indicating if the spectrum should be plotted. |
na.action |
Action to take if NAs exist in the data, the default is to fail. |
returnInternals |
Return the weighted eigencoefficients, complex mean values, and so on. These are necessary for extensions to the multitaper, including magnitude-squared coherence (function mtm.coh in this package). Note: The internal ($mtm) variables eigenCoefs and eigenCoefWt correspond to the multitaper eigencoefficients. The eigencoefficients correspond to equation (3.4) and weights, eigenCoefWt, correspond to sqrt(|d_k(f)|^2) from equation (5.4) in Thomson's 1982 paper. This is because the square root values contained in eigenCoefWt are commonly used in additional calculations (example: eigenCoefWt * eigenCoefs). The values returned in mtm$cmv correspond to the the estimate of the coefficients hat(mu)(f) in equation (13.5) in Thomson (1982), or to the estimate of hat(C)_1 at frequency 1 in equation (499) form Percival and Walden (1993) |
detrend |
Shall the time series data be linearly detrended before
computing the spectrum? Defaults to |
bPad |
Shall the time series data be padded before computing the
spectrum? Defaults to |
... |
further parameters passed to |
an object of class "spec"
, with the additional list component
dof
: a numeric vector of the same length as the spectrum with
the degrees of freedom of the spectral estimate (copied from the
spec.mtm
default output).
Thomas Laepple
Thomson, D.J (1982) Spectrum estimation and harmonic analysis. _Proceedings of the IEEE_ Volume *70*, Number 9, pp. 1055-1096.
Percival, D.B. and Walden, A.T. (1993) _Spectral analysis for physical applications_ Cambridge University Press.
spec.mtm
x <- ts(arima.sim(list(ar = 0.9), 1000))
spec <- proxysnr:::SpecMTM(x)
proxysnr:::LPlot(spec, col = 'grey', ylim = c(0.01, 100))
proxysnr:::LLines(proxysnr:::LogSmooth(spec), lwd = 2)
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