Hi UseRs,
I don't want to die beeing idiot...
I dont understand the different results between: cor() and cov2cov(cov()).
See this little example:
> x=matrix(c(0.5,0.2,0.3,0.1,0.4,NA,0.7,0.2,0.6,0.1,0.4,0.9),ncol=3)
> cov2cor(cov(x,use="pairwise.complete.obs"))
[,1] [,2] [,3]
[1,] 1.0000000 0.4653400 -0.1159542
[2,] 0.4653400 1.0000000 -0.7278728
[3,] -0.1159542 -0.7278728 1.0000000
> cor(x,use="pairwise.complete.obs")
[,1] [,2] [,3]
[1,] 1.0000000 0.3973597 -0.1159542
[2,] 0.3973597 1.0000000 -0.9736842
[3,] -0.1159542 -0.9736842 1.0000000My question arises in a context where cor(mydata, use="pairwise.complete.obs") returns correlations on diagonal that are near 0.95 (where as my data do have 100 observations and only 12 missing values...).
Do cor() and cov() handle the same way the argument "pairwise.complete.obs"?
Eric
R.version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 0.0
year 2004
month 10
day 04
language R
Eric Lecoutre UCL / Institut de Statistique Voie du Roman Pays, 20 1348 Louvain-la-Neuve Belgium
tel: (+32)(0)10473050 [EMAIL PROTECTED] http://www.stat.ucl.ac.be/ISpersonnel/lecoutre
If the statistics are boring, then you've got the wrong numbers. -Edward Tufte
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