NAME

       v.normal  - Tests for normality for vector points.

KEYWORDS

       vector, statistics, points, point pattern

SYNOPSIS

       v.normal
       v.normal --help
       v.normal  [-rl]  map=name   [layer=string]   tests=range[,range,...] column=name  [--help]
       [--verbose]  [--quiet]  [--ui]

   Flags:
       -r
           Use only points in current region

       -l
           Lognormality instead of normality

       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       map=name [required]
           Name of vector map
           Or data source for direct OGR access

       layer=string
           Layer number or name
           Vector features can have category values in different layers. This  number  determines
           which layer to use. When used with direct OGR access this is the layer name.
           Default: 1

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

       column=name [required]
           Name of 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

       Compute  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:
       g.region raster=elevation -p
       v.random random n=200
       v.db.addtable random colum="elev double precision"
       v.what.rast random rast=elevation column=elev
       v.normal random tests=1-3,14 column=elev

SEE ALSO

        v.univar

AUTHOR

       James Darrell McCauley <darrell@mccauley-usa.com>,
       when he was at: Agricultural Engineering Purdue University

       Last changed: $Date: 2014-12-19 22:55:37 +0100 (Fri, 19 Dec 2014) $

       Main index | Vector index | Topics index | Keywords index | Full index

       © 2003-2016 GRASS Development Team, GRASS GIS 7.0.3 Reference Manual