Univariate and Multivariate Spectral Estimation
This is spec.pgram with a few changes in the defaults and written so you can easily extract the estimate of the multivariate spectral matrix as fxx. The bandwidth calculation has been changed to the more practical definition given in the text. Can be used to replace spec.pgram for univariate series.
mvspec(x, spans = NULL, kernel = NULL, taper = 0, pad = 0,
fast = TRUE, demean = FALSE, detrend = TRUE,
plot = TRUE, log='n', type = NULL,
na.action = na.fail, ...)x |
univariate or multivariate time series (i.e., the p columns of x are time series) |
spans |
specify smoothing; same as |
kernel |
specify kernel; same as |
taper |
specify taper; same as |
pad |
specify padding; same as |
fast |
specify use of FFT; same as |
demean |
if TRUE, series is demeaned first; same as |
detrend |
if TRUE, series is detrended first; same as |
plot |
plot the estimate; same as |
log |
same as |
type |
type of plot to be drawn, defaults to lines |
na.action |
same as |
... |
additional arguments; same as |
This is spec.pgram with a few changes in the defaults and written so you can easily extract the estimate of the multivariate spectral matrix as fxx. The default for the plot is NOT to plot on a log scale and the graphic will have a grid. The bandwidth calculation has been changed to the more practical definition given in the text, (L_h/n.used)*frequency(x). Although meant to be used to easily obtain multivariate spectral estimates, this script can be used for univariate time series. Note that the script does not taper by default (taper=0); this forces the user to do "conscious tapering".
An object of class "spec", which is a list containing at least the following components:
fxx |
spectral matrix estimates; an array of dimensions |
freq |
vector of frequencies at which the spectral density is estimated. |
spec |
vector (for univariate series) or matrix (for multivariate series) of estimates of the spectral density at frequencies corresponding to freq. |
details |
matrix with columns: frequency, period, spectral ordinate(s) |
coh |
NULL for univariate series. For multivariate time series, a matrix containing the squared coherency between different series. Column i + (j - 1) * (j - 2)/2 of coh contains the squared coherency between columns i and j of x, where i < j. |
phase |
NULL for univariate series. For multivariate time series a matrix containing the cross-spectrum phase between different series. The format is the same as coh. |
Lh |
Number of frequencies (approximate) used in the band, as defined in Chapter 4. |
n.used |
Sample length used for the FFT |
series |
The name of the time series. |
snames |
For multivariate input, the names of the component series. |
method |
The method used to calculate the spectrum. |
The results are returned invisibly if plot is true.
# real raw periodogram mvspec(soi) mvspec(soi, log='y') # on a log scale # smooth and some details printed mvspec(soi, spans=c(7,7), taper=.5)$details[1:45,] # multivariate example ts.plot(mdeaths, fdeaths, col=1:2) # an R data set, male/female monthly deaths ... dog = mvspec(cbind(mdeaths,fdeaths), spans=c(3,3), taper=.1) dog$fxx # look a spectral matrix estimates dog$bandwidth # bandwidth with time unit = year dog$df # degrees of freedom plot(dog, plot.type="coherency") # plot of squared coherency
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