Full_Name: Christian Lederer Version: 1.8.0 OS: Linux Submission from: (NULL) (217.229.7.13)
R-1.8.0 seems to calculate wrong covariances, when the argument of cov() is a matrix or a data frame. The following should produce a matrix of zeroes and NaNs: x <- matrix(c(NA ,NA ,0.9068995 ,NA ,-0.3116229, -0.06011117 ,0.7310134 ,NA ,1.738362 ,0.6276125, 0.6615581 ,NA ,NA ,-2.646011 ,-2.126105, NA ,1.081825 ,NA ,1.253795 ,1.520708, 0.2822814 ,NA ,NA ,NA ,NA, 0.03291028 ,NA ,NA ,NA ,NA, NA ,NA ,NA ,-0.5462126 ,-0.1997394, NA ,-0.3419413 ,-0.2675226 ,-1.000133 ,-0.1346234, NA ,NA ,-0.411743 ,1.301612 ,NA, 0.922197 ,NA ,0.9513522 ,0.2357021 ,NA), nrow=10, ncol=5) c1 <- cov(x, use="pairwise.complete") c2 <- matrix(nrow=5, ncol=5) for (i in 1:5) { for (j in 1:5) { c2[i,j] <- cov(x[,i], x[,j], use="pairwise.complete") } } c2-c1 Instead, R-1.8.0 produces this result: [,1] [,2] [,3] [,4] [,5] [1,] 0.00000000 -0.03053828 NA -0.0144996353 -0.03485883 [2,] -0.03053828 -0.01649857 NA 0.0137259383 -0.02960707 [3,] NA NA -0.1296134 NA NA [4,] -0.01449964 0.01372594 NA -0.0003152629 0.08717648 [5,] -0.03485883 -0.02960707 NA 0.0871764791 0.04961190 This happens as well under Linux (Suse 9.1) as well as under Windows NT. Under 1.9.1 (Linux) and 1.9.0 (Windows) i get the expected matrix of zeroes and NaNs. This example is not very special. Under R-1.8.0 cov produced wrong result for any random matrix i tried. Doesn't this mean, that *any* result obtained under R 1.8.0 is unreliable? By the way, i just recompiled R-1.8.0 from source under Linux and tried 'make check'. All tests were ok. Does there exist a more detailed set of tests, which could insure that at least the most basic R functions work correctly? Christian ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-devel