.TH LOMB 1 "14 June 1995" "PSD Estimation" "Signal processing"
.SH NAME
lomb \- estimate power spectrum using the Lomb periodogram method
.SH SYNOPSIS
\fBlomb\fR [ \fIoptions ...\fR ] \fIinput-file\fR
.SH DESCRIPTION
.PP
\fIlomb\fR transforms a real-valued time series (from the specified
\fIinput-file\fR, or from the standard input if \fIinput-file\fR is
specified as ``-''; \fIinput-file\fR must be in text form) into a
power spectrum (on the standard output), using a technique known as
the Lomb periodogram [Lomb, N.R., ``Least-squares frequency analysis of
unequally spaced data'', \fIAstrophysics and Space Science\fR 39:447-462
(1976)].
.PP
The input is a text file containing a sampled time series, presented
as two columns of numbers (the sample times and the sample values).
The intervals between consecutive samples need not be uniform (in
fact, this is the most significant advantage of the Lomb periodogram
over other methods of power spectral density estimation).  \fIlomb\fR
writes the Lomb periodogram (the power spectral density estimate
derived from the input time series) on the standard output, in two
columns (frequency and power).  If the units of the sample times in the
input file are seconds, the units of the frequencies in the output are Hz.
.PP
\fIOptions\fR are:
.TP
\fB-h\fR
Print a usage summary.
.TP
\fB-s\fR
Smooth the output.
.PP
The original version of this program was based on the algorithm described in
Press, W.H, and Rybicki, G.B., ``Fast algorithm for spectral analysis of
unevenly sampled data'', \fIAstrophysical J.\fR 338:277-280 (1989).
It has been rewritten using the version of this algorithm presented in
Press, W.H., Teukolsky, S.A., Vetterling, W.T., and Flannery, B.P.,
\fINumerical Recipes in C: the Art of Scientific Computing\fR, pp. 575-584
(Cambridge Univ. Press, 1992).
.PP
Among many other applications, this program can be used to estimate heart
rate power spectra, in combination with \fIihr\fR (see Moody, G.B., ``Spectral
analysis of heart rate without resampling'', \fIComputers in Cardiology
1993\fR, pp. 715-718 (IEEE Computer Society Press, 1993)).  The Lomb method
is ideal for analysis of any time series with missing or noisy data (the noisy
data may be removed from the time series and need not be replaced, as would be
necessary if conventional PSD estimation algorithms were employed).
.SH SEE ALSO
fft(1), hrfft(1), memse(1)
.SH AVAILABILITY
.PP
This program is part of the \fIpsd\fR package, distributed with the DB
Software Package, version 9.3 and later.