The periodogram is a classical tool
based on the sample Fourier transform
for finding periodic components in a time series.
pgram computes and plots an average
of np periodograms where
np=floor(length(x)/fftlen) where the
fftlen is the length of the FFT; to get just
1 FFT of length
x(1:fftlen) in place of
x. To get a
significance of high periodogram peaks, the procedure tests,
at each frequency, the value of the averaged periodogram against
the average of
2*halflen neighboring cells (
halflen on each side),
and averaged over the np periodograms; the neighboring cell average
is called the background. Significance of the ratio of center
frequency average to the background average is computed from the
input time series, missing values denoted by NaNs will be
length of FFT which will be used. In
other arguments that are connected with periodogram plot:
When we assume that period
T of PC-T structure is unknown,
pgram enables us to find
candidate for the period length assuming the period of
the second order structure is the same as the period of
the first order structure (IE, in the series itself).
For any FFT index j (say where a strong peak occurs)
j corresponds to the number of cycles in the FFT window,
so the period can be easily computed as
T = fftlen/j.
Box, G. E. P., Jenkins, G. M., Reinsel, G. (1994), Time Series Analysis, 3rd Ed., Prentice-Hall,
Englewood Cliffs, NJ.
Hurd, H. L., Miamee, A. G., (2007), Periodically Correlated Random Sequences: Spectral Theory and Practice, Wiley InterScience.
1 2 3
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.