Glynn,
I have seen the r.series extension (much welcome) and tested it after
backport with:
GRASS 6.4.svn (nc_spm_07):~ > g.region n=230000 s=214000 w=628000
e=646000 nsres=2000 ewres=2000 -p
# numbers taken from
http://www.nabble.com/-R--problems-with-garchFit-td7497741.html#a7501094
i=0
for n in `cat numbers.asc` ; do
i=`expr $i + 1`
r.mapcalc "map$i=double($n)"
done
r.series in=`g.mlist type=rast pat="map*" sep=','` out=skew meth=skewness
r.info -r skew
min=-0.639793
max=-0.639793
R
mynum <- read.csv("numbers.asc", header=FALSE)
str(mynum)
'data.frame': 202 obs. of 1 variable:
$ V1: num 0.01071 0.02384 0.01709 0.01387 -0.00210 ...
skewness(mynum$V1)
[1] -0.6371108
Is the subtle difference a precision problem somewhere?
Markus
(attachments)
numbers.asc.gz (1.86 KB)
Markus Neteler wrote:
I have seen the r.series extension (much welcome) and tested it after
backport with:
GRASS 6.4.svn (nc_spm_07):~ > g.region n=230000 s=214000 w=628000
e=646000 nsres=2000 ewres=2000 -p
# numbers taken from
http://www.nabble.com/-R--problems-with-garchFit-td7497741.html#a7501094
i=0
for n in `cat numbers.asc` ; do
i=`expr $i + 1`
r.mapcalc "map$i=double($n)"
done
r.series in=`g.mlist type=rast pat="map*" sep=','` out=skew meth=skewness
r.info -r skew
min=-0.639793
max=-0.639793
R
> mynum <- read.csv("numbers.asc", header=FALSE)
> str(mynum)
'data.frame': 202 obs. of 1 variable:
$ V1: num 0.01071 0.02384 0.01709 0.01387 -0.00210 ...
> skewness(mynum$V1)
[1] -0.6371108
Is the subtle difference a precision problem somewhere?
I think that it's due to the difference between sample and population
variants of the standard deviation calculation.
I used the "population" definitions, which divide by N rather than N-1
when calculating the standard deviation. This is consistent with the
variance and standard deviation functions already provided by
lib/stats (and used by r.series).
FWIW, I get -0.641871 for /N and -0.637111 for /(N-1). The latter
matches the result from R. I'm not sure where you get -0.639793 from
(maybe there's a stray comma in the file?).
I notice that v.univar displays both the sample and population
variants of the variance and standard deviation, but only the sample
variant is given for skewness and kurtosis.
--
Glynn Clements <glynn@gclements.plus.com>