This is the command v.normalgrass that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
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
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