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<h2>NAME</h2>
<em><b>v.normal</b></em> - Tests for normality for points.
<h2>KEYWORDS</h2>
vector, statistics
<h2>SYNOPSIS</h2>
<b>v.normal</b><br>
<b>v.normal help</b><br>
<b>v.normal</b> [-<b>rql</b>] <b>map</b>=<em>string</em> <b>tests</b>=<em>range</em>[,<i>range</i>,...] <b>column</b>=<em>string</em> [--<b>verbose</b>] [--<b>quiet</b>]
<h3>Flags:</h3>
<DL>
<DT><b>-r</b></DT>
<DD>Use only points in current region</DD>
<DT><b>-q</b></DT>
<DD>Quiet</DD>
<DT><b>-l</b></DT>
<DD>lognormal</DD>
<DT><b>--verbose</b></DT>
<DD>Verbose module output</DD>
<DT><b>--quiet</b></DT>
<DD>Quiet module output</DD>
</DL>
<h3>Parameters:</h3>
<DL>
<DT><b>map</b>=<em>string</em></DT>
<DD>point vector defining sample points</DD>
<DT><b>tests</b>=<em>range[,<i>range</i>,...]</em></DT>
<DD>Lists of tests (1-15): e.g. 1,3-8,13</DD>
<DT><b>column</b>=<em>string</em></DT>
<DD>Attribute column</DD>
</DL>
<H2>DESCRIPTION</H2>
<EM>v.normal</EM>
computes tests of normality on vector points.
<H2>NOTES</H2>
The tests that <EM>v.normal</EM> performs are indexed
below. The tests that are performed are specified by
giving an index, ranges of indices, or multiple thereof.
<OL>
<LI> Sample skewness and kurtosis
<LI> Geary's a-statistic and an approximate normal transformation
<LI> Extreme normal deviates
<LI> D'Agostino's D-statistic
<LI> Modified Kuiper V-statistic
<LI> Modified Watson U^2-statistic
<LI> Durbin's Exact Test (modified Kolmogorov)
<LI> Modified Anderson-Darling statistic
<LI> Modified Cramer-Von Mises W^2-statistic
<LI> Kolmogorov-Smirnov D-statistic (modified for normality testing)
<LI> Chi-Square test statistic (equal probability classes) and
the number of degrees of freedom
<LI> Shapiro-Wilk W Test
<LI> Weisberg-Binghams W'' (similar to Shapiro-Francia's W')
<LI> Royston's extension of W for large samples
<LI> Kotz Separate-Families Test for Lognormality vs. Normality
</OL>
<H2>EXAMPLE</H2>
<!-- do a meaning ful example -->
<div class="code"><pre>
v.random random n=200
v.db.addtable random col="elev double precision"
v.what.rast random rast=elevation.10m col=elev
v.normal random tests=1-3,14 col=elev
</pre></div>
computes the sample skewness and kurtosis, Geary's
a-statistic and an approximate normal transformation,
extreme normal deviates, and Royston's W for the
<EM>random</EM> vector points.
<!-- TODO: find references , e.g.
http://www.itl.nist.gov/div898/handbook/eda/section3/eda35.htm
-->
<H2>SEE ALSO</H2>
<A HREF="v.univar.html">v.univar</A>
<H2>AUTHOR</H2>
<A HREF="http://mccauley-usa.com/">James Darrell McCauley</A>
<A HREF="mailto:darrell@mccauley-usa.com"><darrell@mccauley-usa.com></A>,
<br>when he was at:
<A HREF="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural
Engineering</A>
<A HREF="http://www.purdue.edu/">Purdue University</A>
<p><i>Last changed: $Date: 2007-03-20 07:18:19 +0100 (Tue, 20 Mar 2007) $</i>
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