Usage
spec.mtm(timeSeries, nw=4.0, k=7, nFFT="default", taper=c("dpss"),
centre=c("Slepian"), dpssIN=NULL, returnZeroFreq=TRUE,
Ftest=FALSE, jackknife=FALSE, jkCIProb=.95, adaptiveWeighting=TRUE,
maxAdaptiveIterations=100, plot=TRUE, na.action=na.fail,
returnInternals=FALSE, sineAdaptive=FALSE, sineSmoothFact=0.2,
dtUnits=c("default"), deltat=NULL, ...)Arguments
timeSeries
A time series of equally spaced data, this can be
created by the ts() function where deltat is specified.
nw
nw a positive double precision number, the time-bandwidth
parameter.
k
k a positive integer, the number of tapers, often 2*nw.
nFFT
This function pads the data before computing the fft. nFFT
indicates the total length of the data after padding.
taper
Choose between dpss-based multitaper (the default,'dpss') or sine taper
method. In the case of the sine taper, parameter nw is useless, and both Ftest
and jackknife are forced to FALSE. The sine taper also has two specific parameters
below.
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.
adaptiveWeighting
Boolean flag for enabling/disabling adaptively weighted
spectrum estimates. Defaults to TRUE. The FALSE case gives complex
Fourier transforms equivalent to direct estimates with Slepian sequences as tapers.
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 eigenCoe
sineAdaptive
In the case of using the sine taper method, choose between
non-adaptive and adaptive taper choice.
sineSmoothFact
The sine taper option has an inherent smoothing parameter that
can be set between 0.01 and 0.5. Lower values indicate smaller amounts of smoothing.
dtUnits
Allows indication of the units of delta-t for accurate frequency axis
labels.
deltat
Time step for observations. If not in seconds, dtUnits should be set to indicate
the proper units for plot labels.
...
Additional parameters, such as xaxs="i" which are passed to
the plotting function. Not all parameters are supported.