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 <[EMAIL PROTECTED]> _______________________________________________ grass-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-dev
