Description Usage Arguments Details Value Note Author(s) References See Also Examples
The most commonly used method of computing the spectrum on unevenly spaced time series is periodogram analysis, see Lomb (1975) and Scargle (1982). The LombScargle method for unevenly spaced data is known to be a powerful tool to find, and test significance of, weak perriodic signals. The LombScargle periodogram possesses the same statistical properties of standard power spectra.
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x 
two column data frame or matrix with the first column
being the sampled time and the second column being the observations at
the first column; otherwise 
y 
not used if 
spans 
vector of odd integers giving the widths of modified Daniell smoothers to be used to smooth the periodogram. 
kernel 
alternatively, a kernel smoother of class

taper 
proportion of data to taper. A split cosine bell taper is applied to this proportion of the data at the beginning and end of the series. 
pad 
proportion of data to pad. Zeros are added to the end of
the series to increase its length by the proportion 
fast 
logical; if 
type 
LombScargle spectrum of Fourier transformation spectrum 
demean 
logical. If 
detrend 
logical. If 
plot.it 
plot the periodogram? 
na.action 

... 
graphical arguments passed to 
The raw LombScargle periodogram for irregularly sampled time series is not a consistent estimator of the spectral density, but adjacent values are asymptotically independent. Hence a consistent estimator can be derived by smoothing the raw periodogram, assuming that the spectral density is smooth.
The series will be automatically padded with zeros until the series
length is a highly composite number in order to help the Fast Fourier
Transform. This is controlled by the fast
and not the pad
argument.
The periodogram at zero is in theory zero as the mean of the series is removed (but this may be affected by tapering): it is replaced by an interpolation of adjacent values during smoothing, and no value is returned for that frequency.
A list object of class "spec.ls"
with the following additional components:
kernel 
The 
df 
The distribution of the spectral density estimate can be
approximated by a chi square distribution with 
bandwidth 
The equivalent bandwidth of the kernel smoother as defined by Bloomfield (1976, page 201). 
taper 
The value of the 
pad 
The value of the 
detrend 
The value of the 
demean 
The value of the 
The result is returned invisibly if plot.it
is true.
This is 'slow' program and a fast program may use FFT, see (Press et al, 1992)
LombScargle periodogram by Zhu Wang
Bloomfield, P. (1976) Fourier Analysis of Time Series: An Introduction.Wiley.
Lomb, N. R. (1976) Leastsquares frequencyanalysis of unequally spaced data. Astrophysics and Space Science, 39,447462
W. H. Press and S. A. Teukolsky and W. T. Vetterling and B.P. Flannery (1992) Numerical Recipes in C: The Art of Scientific Computing., Cambridge University Press, second edition.
Scargle, J.D. (1982) Studies in astronomical time series analysis II. Statistical aspects of spectral analysis of unevenly spaced data, The Astrophysical Journal, 263, volume 2, 835853.
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