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v.normal(1grass) Grass User's Manual v.normal(1grass)

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 column="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: 2016-11-14 00:09:36 +0100 (Mon, 14 Nov 2016) $

SOURCE CODE

Available at: v.normal source code (history)

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© 2003-2016 GRASS Development Team, GRASS GIS 7.2.0 Reference Manual

GRASS 7.2.0