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eso-midas-doc-13SEPpl1.2-3.mga5.i586.rpm

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<H2><A NAME="SECTION001748000000000000000">&#160;</A><A NAME="s:util">&#160;</A>
<BR>
Auxiliary utilities
</H2>

<P>
The following commands implement auxiliary utilities for time series 
analysis:
<DL>
<DT><STRONG><TT>BAND/TSA</TT> -</STRONG>
<DD><B>Frequency grid:</B> 
The frequency grid suitable for the analysis of evenly sampled
observations is well determined. However, for uneven sampling no
simple rules exist in general. <TT>BAND/TSA</TT> may be used to find a
reasonable guess for the frequency grid. The results are returned in
the keywords START, STEP and NSTEPS. <TT>BAND/TSA</TT> may err, as usual
in guessing; its results must be checked for consistency.
<DT><STRONG><TT>COVAR/TSA</TT> -</STRONG>
<DD><B>Correlation length:</B>
The statistical evaluation of TSA results rests on the assumption that
the noise in the data is white noise. However, quite often this
assumption is wrong. One way to test its justification is to compute
the residuals from the model fit (e.g. by using <TT>SINEFIT/TSA</TT>)
and to examine the correlation length in the residuals from the
autocorrelation function (ACF; computed with <TT>COVAR/TSA</TT>). The
average number of observations per correlation length is the average
number of correlated observations <I>n</I><SUB><I>corr</I></SUB>.  For white noise this
number should be of order&nbsp;1.
<DT><STRONG><TT>NORMALIZE/TSA</TT> -</STRONG>
<DD><B>Normalize mean &amp; variance:</B>
Normalize mean and (optionally) variance of a column to 0 and 1,
respectively.  Subtraction of the average value from the data is
always recommended for numerical reasons. Certain commands will not
work correctly for large mean values. Normalization of the variances to
the same unit value is required for <TT>DELAY/TSA</TT>.  
<DT><STRONG><TT>SINEFIT/TSA</TT> -</STRONG>
<DD><B>Filtering of the series:</B> 
This versatile command may be used not only for parameter estimation
but also for data massaging. <TT>SINEFIT/TSA</TT> may also be used to
remove a trend from data (high pass filtering). For this purpose
choose a low value for frequency, so that only few cycles cover the
time interval spanned by the observations.  Specify just 1 iteration,
so that the routine does not attempt a frequency correction.
Subtraction of such data from the raw data returns the fitted trend
(low pass filtering).  The results are in a format suitable for
renewed input to the other frequency domain TSA commands.  
<DT><STRONG><TT>WIDTH/TSA</TT> -</STRONG>
<DD><B>Width of spectral lines:</B> 
Profiles of spectral lines appearing in test statistics may be used to
refine signal parameters and their errors. In its present primitive
form, this command analyses the strongest maximum (an 'emission' line)
in the specified sub-spectrum.  The window should not be too
narrow as it is also used for the determination of the continuum
level.  A comparison of the continuum level with the expected value of
the statistic for a pure noise signal may reveal interference and/or
noise correlation. The width of the line may be used to estimate
confidence interval of the frequency associated with the line.
However, note that the width at half intensity is generally not a good
estimate.  For Scargle's statistic and power spectra use the width at
the level corresponding to the peak level minus the average noise
level <I>P</I>-<I>N</I> (Schwarzenberg-Czerny, 1991). For this purpose, this
command returns a small table of widths on the screen and in keyword
<TT>OUTPUTR</TT>.  In power spectra, the peak height of the line is a
good measure of the square of the amplitude of the oscillation. - An
'absorption' line can be converted into a 'emission' line by simply
changing the sign with <TT>COMPUTE/TABLE</TT>.
</DL>
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<I>Petra Nass</I>
<BR><I>1999-06-15</I>
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