Compute the power spectral density of an autoregressive model.
ar_psd(
a,
v = 1,
freq = 256,
fs = 1,
range = ifelse(is.numeric(a), "half", "whole"),
method = ifelse(length(freq) == 1 && bitwAnd(freq, freq - 1) == 0, "fft", "poly")
)# S3 method for ar_psd
plot(
x,
yscale = c("linear", "log", "dB"),
xlab = NULL,
ylab = NULL,
main = NULL,
...
)
numeric vector of autoregressive model coefficients. The first element is the zero-lag coefficient, which always has a value of 1.
square of the moving average coefficient, specified as a positive scalar Default: 1
vector of frequencies at which power spectral density is calculated, or a scalar indicating the number of uniformly distributed frequency values at which spectral density is calculated. Default: 256.
sampling frequency (Hz). Default: 1
character string. one of:
"half" or "onesided"frequency range of the spectrum
is from zero up to but not including fs / 2. Power from negative
frequencies is added to the positive side of the spectrum.
"whole" or "twosided"frequency range of the spectrum
is -fs / 2 to fs / 2, with negative frequencies stored in
"wrap around order" after the positive frequencies; e.g. frequencies for a
10-point "twosided" spectrum are 0 0.1 0.2 0.3 0.4 0.5 -0.4 -0.3
-0.2. -0.1.
"shift" or "centerdc"same as "whole" but with
the first half of the spectrum swapped with second half to put the
zero-frequency value in the middle. If freq is a vector,
"shift" is ignored.
Default: If model coefficients a are real, the default range is
"half", otherwise the default range is "whole".
method used to calculate the power spectral density, either
"fft" (use the Fast Fourier Transform) or "poly" (calculate
the power spectrum as a polynomial). This argument is ignored if the
freq argument is a vector. The default is "poly" unless the
freq argument is an integer power of 2.
object to plot.
character string specifying scaling of Y-axis; one of
"linear", "log", "dB"
labels passed to plotting function. Default: NULL
additional arguments passed to functions
An object of class "ar_psd" , which is a list containing two
elements, freq and psd containing the frequency values and
the estimates of power-spectral density, respectively.
This function calculates the power spectrum of the autoregressive model
M
x(n) = sqrt(v).e(n) + SUM a(k).x(n-k)
k=1
where x(n) is the output of the model and e(n) is white noise.# NOT RUN {
a <- c(1, -2.7607, 3.8106, -2.6535, 0.9238)
psd <- ar_psd(a)
# }
Run the code above in your browser using DataLab