SpecMTM | R Documentation |
calls spec.mtm
from library multitaper
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 = 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 |
a positive integer, the number of tapers, often 2*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 |
logical, detrend timeseries before estimating the spectrum |
bPad |
if FALSE (the default) nFFT is set to the length of the timeseries |
... |
additional arguments to multitaper::spec.mtm |
spectra object list(freq, spec, dof)
Thomas Laepple
Other functions to estimate power spectra:
SpecACF()
x <- ts(arima.sim(list(ar = 0.9), 1000))
spec <- SpecMTM(x)
LPlot(spec, col='grey')
LLines(LogSmooth(spec), lwd=2)
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