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...d to both. My attempt below fails. df <- data.frame(matrix(rnorm(40), 10, 4), f1 = gl(3, 10, labels = letters[1:3]), f2 = gl(3, 10, labels = letters[4:6])) df %>% group_by(f1, f2) %>% summarise(x1m = mean(X1), x2m = mean(X2), x3m = mean(X3), x4m = mean(X4)) df %>% group_by(f1) %>% summarise(x1m = mean(X1), x2m = mean(X2), x3m = mean(X3), x4m = mean(X4)) # My fail attempt s <- function() { dplyr::summarise(x1m = mean(X1), x2m = mean(X2),...

...i Lars, Two comments: 1. You can achieve what you want with a slight modification of your definition of s(), using the hint from the error message that you need an argument '.': s <- function(.) { dplyr::summarise(., x1m = mean(X1), x2m = mean(X2), x3m = mean(X3), x4m = mean(X4)) } 2. You have not given a great test case in how you set your two factors because the two group_by()'s will give the identical groupings, An alternative which confirms that the function s() does what you want might be: df <- data.frame(matrix(...

...- data.frame(matrix(rnorm(40), 10, 4), > f1 = gl(3, 10, labels = letters[1:3]), > f2 = gl(3, 10, labels = letters[4:6])) > > > df %>% > group_by(f1, f2) %>% > summarise(x1m = mean(X1), > x2m = mean(X2), > x3m = mean(X3), > x4m = mean(X4)) > > df %>% > group_by(f1) %>% > summarise(x1m = mean(X1), > x2m = mean(X2), > x3m = mean(X3), > x4m = mean(X4)) > > # My fail attempt > > s <- function() { > dplyr::su...

...share path = /home/shares/sagedata writeable = yes browseable = no valid users = @accdept @ntadmins write list = @accdept @ntadmins create mask = 0771 directory mask = 0771 veto oplock files = /*.mdb/*.MDB/*.ldb/*.LDB locking = yes share modes = yes -- Best regards Fredrik von Kantzow X3m Networks #84 Sheraton Park Christ Church Barbados W.I. Main: +1 246 435 7076 Cell: +1 246 257 5463 WWW : http://x3m.net Mail: fredrik@x3m.net

...re than 3 factors) library("sem") #put in "mydata", the value of the questions mydata <- data.frame(X$X12a,X$X12b,X$X12c,X$X12d,X$X12e,X$X12f,X$X12g,X$X12h,X$X12i,X$X12l,X$X12m,X$X12n,X$X12o,X$X12p,X$X12q,X$X12r,X$X12s,X$X1a,X$X1b,X$X1c,X$X1d,X$X1e,X$X1f,X$X3h,X$X3i,X$X3l,X$X3m,X$X3n,X$X3o,X$X3p,X$X3q,X$X3r,X$X3s,X$X3t,X$X3u,X$X3v,X$X4a,X$X5q,X$X5r,X$X5s,X$X8a,X$X8b,X$X8c,X$X8d) #i calculate the covariance of the data mydata.cov <- cov(mydata,use="complete.obs") #I specify my model model.mydata <- specify.model() F1 -> X.X12a, lam1, NA F1 -> X.X12...

...ore than 3 factors) library("sem") #put in "mydata", the value of the questions mydata <- data.frame(X$X12a,X$X12b,X$X12c,X$X12d,X$X12e,X$X12f,X$X12g,X$X12h,X$X12i,X$X12l,X$X12m,X$X12n,X$X12o,X$X12p,X$X12q,X$X12r,X$X12s,X$X1a,X$X1b,X$X1c,X$X1d,X$X1e,X$X1f,X$X3h,X$X3i,X$X3l,X$X3m,X$X3n,X$X3o,X$X3p,X$X3q,X$X3r,X$X3s,X$X3t,X$X3u,X$X3v,X$X4a,X$X5q,X$X5r,X$X5s,X$X8a,X$X8b,X$X8c,X$X8d) #i calculate the covariance of the data mydata.cov <- cov(mydata,use="complete.obs") #I specify my model model.mydata <- specify.model() F1 ->  X.X12a, lam1, NA F1 ->  X.X12...

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking