NAME

       v.normal  - Tests for normality for points.

KEYWORDS

       vector, statistics

SYNOPSIS

       v.normal
       v.normal help
       v.normal [-rql] map=string tests=range[,range,...] column=string  [--verbose]  [--quiet]

   Flags:
       -r
           Use only points in current region

       -q
           Quiet

       -l
           lognormal

       --verbose
           Verbose module output

       --quiet
           Quiet module output

   Parameters:
       map=string
           point vector defining sample points

       tests=range[,range,...]
           Lists of tests (1-15): e.g. 1,3-8,13

       column=string
           Attribute column

DESCRIPTION

       v.normal computes tests of normality on vector points.

NOTES

       The  tests  that  v.normal  performs  are indexed below.  The tests that are performed are
       specified by giving an index, ranges of indices, or multiple thereof.

       1
               Sample skewness and kurtosis

       2
               Geary's a-statistic and an approximate normal transformation

       3
               Extreme normal deviates

       4
               D'Agostino's D-statistic

       5
               Modified Kuiper V-statistic

       6
               Modified Watson U^2-statistic

       7
               Durbin's Exact Test (modified Kolmogorov)

       8
               Modified Anderson-Darling statistic

       9
               Modified Cramer-Von Mises W^2-statistic

       10
               Kolmogorov-Smirnov D-statistic (modified for normality testing)

       11
               Chi-Square test statistic (equal probability classes) and the number of degrees of
              freedom

       12
               Shapiro-Wilk W Test

       13
               Weisberg-Binghams W'' (similar to Shapiro-Francia's W')

       14
               Royston's extension of W for large samples

       15
               Kotz Separate-Families Test for Lognormality vs. Normality

EXAMPLE

       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
         computes the sample skewness and kurtosis, Geary's a-statistic and an approximate normal
       transformation, extreme normal deviates, and Royston's W for the random vector points.

SEE ALSO

       v.univar

AUTHOR

       James Darrell McCauley ,
       when he was at: Agricultural Engineering Purdue University

       Last changed: $Date: 2011-11-08 03:29:50 -0800 (Tue, 08 Nov 2011) $

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