inst/Examples/rdex_normalization.R

In psd: Adaptive, Sine-Multitaper Power Spectral Density and Cross Spectrum Estimation

\dontrun{#REX
library(psd)

##
## Normalization
##

# timeseries with sampling frequency **not** equal to 1:
set.seed(1234)
X <- ts(rnorm(1e3), frequency=20)

# spec.pgram: double sided
pgram <- spectrum(X)

# psdcore: single sided
PSD <- psdcore(X)

# note the normalization differences:
plot(pgram, log="dB", ylim=c(-40,10))
plot(PSD, add=TRUE, col="red", log="dB")

# A crude representation of integrated spectrum: 
#   should equal variance of white noise series (~= 1)
mean(pgram[['spec']]) * max(pgram[['freq']])
mean(PSD[['spec']]) * max(PSD[['freq']])

# normalize 
pgram <- normalize(pgram, src="spectrum")
PSD <- normalize(pgram, src="psd")
# replot them
plot(pgram, log="dB", ylim=c(-40,10))
plot(PSD, add=TRUE, col="red", log="dB")

# Again, integrated spectrum should be ~= 1:
mean(pgram[['spec']]) * max(pgram[['freq']])
mean(PSD[['spec']]) * max(PSD[['freq']])


}#REX