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.
- Sample skewness and kurtosis
- Geary's a-statistic and an approximate normal transformation
- Extreme normal deviates
- D'Agostino's D-statistic
- Modified Kuiper V-statistic
- Modified Watson U^2-statistic
- Durbin's Exact Test (modified Kolmogorov)
- Modified Anderson-Darling statistic
- Modified Cramer-Von Mises W^2-statistic
- Kolmogorov-Smirnov D-statistic (modified for normality testing)
- Chi-Square test statistic (equal probability classes) and
the number of degrees of freedom
- Shapiro-Wilk W Test
- Weisberg-Binghams W'' (similar to Shapiro-Francia's W')
- Royston's extension of W for large samples
- 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 00:05:32 +0100 (Mon, 14 Nov 2016) $