mtmAR | R Documentation |
Perform the 'intermediate spectrum test' of Thomson et al. (2001).
Paraphrased from Thomson et al. (2001): Form an intermediate spectrum by dividing MTM by AR estimate. Choose an order P for a predictor. A variety of formal methods are available in the literature, but practically, one keeps increasing P (the order) until the range of the intermediate spectrum Si(f) (equation (C4) of Thomson et al., 2001) stops decreasing rapidly as a function of P. If the intermediate spectrum is not roughly white, as judged by the minima, the value of P should be increased.
mtmAR(dat,tbw=3,ntap=NULL,order=1,method="mle",CItype=1,padfac=5,demean=T,detrend=F,
output=1,xmin=0,xmax=Nyq,pl=1,genplot=T,verbose=T)
dat |
Stratigraphic series for analysis. First column should be location (e.g., depth), second column should be data value. |
tbw |
MTM time-bandwidth product. |
ntap |
Number of DPSS tapers to use. By default, this is set to (2*tbw)-1. |
order |
Order of the AR spectrum. |
method |
AR method ("yule-walker", "burg", "ols", "mle", "yw") |
CItype |
Illustrate (1) one-sided or (2) two-sided confidence intervals on plots |
padfac |
Pad with zeros to (padfac*npts) points, where npts is the original number of data points. |
demean |
Remove mean from data series? (T or F) |
detrend |
Remove linear trend from data series? (T or F) |
output |
Output (1) intermediate spectrum and confidence levels, (2) intermediate spectrum, (3) confidence levels |
xmin |
Smallest frequency for plotting. |
xmax |
Largest frequency for plotting. |
pl |
Plot logarithm of spectral power (1) or linear spectral power (2)? |
genplot |
Generate summary plots? (T or F) |
verbose |
Verbose output? (T or F) |
The power spectrum normalization approach applied here divides the Fourier coefficients by the number of points (npts) in the stratigraphic series, which is equivalent to dividing the power by (npts*npts). The (npts*npts) normalization has the convenient property whereby – for an unpadded series – the sum of the power in the positive frequencies is equivalent to half of variance; the other half of the variance is in the negative frequencies.
Note that the 'spec.mtm' function in package 'multitaper' (Rahim et al., 2014) is used for MTM spectrum estimation.
Rahim, K.J. and Burr W.S. and Thomson, D.J., 2014, Applications of Multitaper Spectral Analysis to Nonstationary Data. PhD thesis, Queen's University. R package version 1.0-17, https://CRAN.R-project.org/package=multitaper.
Thomson, D. J., L. J. Lanzerotti, and C. G. Maclennan, 2001, The interplanetary magnetic field: Statistical properties and discrete modes, J. Geophys.Res., 106, 15,941-15,962, doi:10.1029/2000JA000113.
eha
, lowspec
, mtm
, mtmML96
, and periodogram
# generate example series with periods of 400 ka, 100 ka, 40 ka and 20 ka
ex = cycles(freqs=c(1/400,1/100,1/40,1/20),start=1,end=1000,dt=5)
# add AR1 noise
noise = ar1(npts=200,dt=5,sd=.5)
ex[2] = ex[2] + noise[2]
# MTM spectral analysis, with conventional AR1 noise test
pl(1,title="mtmAR")
mtmAR(ex)
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