search for: combs

Using R 2.6.2, say I have the following list of lists, "comb": data1 <- list(a = 1, b = 2, c = 3) data2 <- list(a = 4, b = 5, c = 6) data3 <- list(a = 3, b = 6, c = 9) comb <- list(data1 = data1, data2 = data2, data3 = data3) So that all names for the lowest level list are common. How can I most efficiently access all of the sublist items "a" indexed by the outer

Hi, all When I am using mle.cv(wle), I find a interesting problem: I can't do leave-one-out cross-validation with mle.cv(wle). I will illustrate the problem as following: > xx=matrix(rnorm(20*3),ncol=3) > bb=c(1,2,0) > yy=xx%*%bb+rnorm(20,0,0.001)+0 > summary(mle.cv(yy~xx,split=nrow(xx)-1,monte.carlo=2*nrow(xx),verbose=T), num.max=1)[[1]] mle.cv: dimension of the split subsample

Thanks alot. How can we view those optimization which are enabled when we do llc -O3 comb.ll Are these the same as the ones produced by the following command line llvm-as < /dev/null | opt -O3 -disable-output -debug-pass=Arguments Regards Shahzad On Tue, Jun 12, 2012 at 1:01 PM, Duncan Sands <baldrick at free.fr> wrote: >> Yes. But how exactly code generation (optimized one)

...   1    1   1 these 2 matrices are identical because i change the first 2 columns   1  -1  1  1      -1  -1   -1  -1 -1  -1 -1 -1       -1   1    1   1   1  1    1  1       1   1    1   1 these 2 matrices are identical because i change the first 2 columns and the first two rows. i wrote this two combs.c <- combn(ncol(m1), 2)     nc <- ncol(combs.c)     ind.c <- vector("logical", nc)     for (i in 1:nc) {         m <- m1         m[, combs.c[, i]] <- m[, rev(combs.c[, i])]         ind.c[i] <- all(m == m2)     }     combs.r <- combn(nrow(m1), 2)     nr <- ncol(comb...

Thanks again. I executed the following command line llc -O3 comb.ll.bc -debug-pass=Arguments and got Pass Arguments: -targetdata -targetpassconfig -no-aa -tbaa -targetlibinfo -basicaa -collector-metadata -machinemoduleinfo -machine-branch-prob -preverify -domtree -verify -loops -loop-simplify -scalar-evolution -loop-simplify -iv-users -loop-reduce -gc-lowering -unreachableblockelim

Two posts in one day is not a good day...and this question seems like it should have an obvious answer: I have a matrix where rows are unique combinations of 1's and 0's: > combs=as.matrix(expand.grid(c(0,1),c(0,1))) > combs Var1 Var2 [1,] 0 0 [2,] 1 0 [3,] 0 1 [4,] 1 1 I want a single function that will give the row index containing an exact match with vector x: > x=c(0,1) The solution needs to be applied many times, so I need somethin...

Hi, On 12/06/12 13:09, Abdul Wahid Memon wrote: > Thanks alot. How can we view those optimization which are enabled when we do > > llc -O3 comb.ll llc -O3 comb.ll -debug-pass=Arguments > > Are these the same as the ones produced by the following command line no, as I mentioned before they are of a completely different nature to the optimizations that opt does. Ciao, Duncan.

Hi, > I executed the following command line > > llc -O3 comb.ll.bc -debug-pass=Arguments > > and got > > Pass Arguments: -targetdata -targetpassconfig -no-aa -tbaa > -targetlibinfo -basicaa -collector-metadata -machinemoduleinfo > -machine-branch-prob -preverify -domtree -verify -loops -loop-simplify > -scalar-evolution -loop-simplify -iv-users -loop-reduce

Hi friends, I need to generate a list, that should contain the quantile value of one column in a data frame. while I am compiling this one i am facing one bug,, Really I cannot find out that where the problem has occurred? Could any one help me to come out from this bug?? Here is the code, data <- lapply(comb.data$zFE, function(x) aggregate(x,

Hi Yes. But how exactly code generation (optimized one) be done without clang. Is it possible that we can specify those optimization (individual ones instead of standard ones like -O3) some how when generating code as is done by clang or llc? Regards Shahzad On Tue, Jun 12, 2012 at 12:42 PM, Duncan Sands <baldrick at free.fr> wrote: > Hi, the reason is that lli does optimized code

Hi, ? Is there some easy way to split the grid.newpage() into two columns? For example, how could I put the two forest plots below (meta1 and meta2) next to each other? library(meta) data(Olkin95) meta1 <- metabin(event.e, n.e, event.c, n.c,data=Olkin95, subset=c(41,47,51,59),sm="RR", meth="I",studlab=author) meta2=meta1 meta2$studlab=rep("",length(meta1$studlab)

> Yes. But how exactly code generation (optimized one) be done without > clang. Is it possible that we can specify those optimization > (individual ones instead of standard ones like -O3) some how when > generating code as is done by clang or llc? llc comb.ll gcc -o comb comb.s Variants: llc -O0 comb.ll llc -O3 comb.ll etc Note that the codegen level optimizations done by llc

Hi, I need some help on integrating a function that is a vector. I have a function - vector which each element is different. And, naturally, function integrate() does not work I checked the article of U. Ligges and J. Fox (2008) about code optimization "How Can I Avoid This Loop or Make It Faster?" on http://promberger.info/files/rnews-vectorvsloops2008.pdf. Their advice did not help

Hi, I have many files containing one column of data. I like to use the scan function to parse the data. Next I like to bind to a large vector. I try this like: count<-1 files <- list.files() # all files in the working directory for(i in files) { tmp <- scan(i) assign(files[count], tmp) count<-count+1 } This part works! Now I like to plot the data in a boxplot.

Dear, I'm starting on R language. I would like some help to implement a MLE function. I wish to obtain the variables values (alpha12, w_g12, w_u12) that maximize the function LL = Y*ln(alpha12 + g*w_g12 + u*w_u12). Following the code: rm(list=ls()) ls() library(stats4) Model = function(alpha12,w_g12,w_u12) { Y = 1 u = 0.5 g = -1 Y*log(alpha12 + g*w_g12 + u*w_u12) } res =

Trying to do a meta-analysis of correlations in R using the meta package; have tried several things and keep getting a similar error. Can anyone help explain the error? > cor<-c(-0.3018, 0.667, -3.8002, -0.607, -0.4885, -3.8002, -0.0701, 0.1348, -0.9505, -0.5709, -0.6127, -1.2419, -0.1511, -0.1054)> n<-c(3,4,3,3,3,3,16,36,30,9,3,3,30,4)> library(meta)> metacor(cor, n, data=NULL,

I can think of many brute-force ways to do this outside of R, but was wondering if there was a simple/elegant solution within R instead. I have a table that looks something like the following: Factor1 Factor2 Value A 11/11/2009 5 A 11/12/2009 4 B 11/11/2009 7 B 11/13/2009 8 >From that I need to generate all permutations of Factor1 and Factor2 and force a 0 for any combination that doesn?t

I need to save data in fixed-width format without headers and reading the help archive leads me to believe that sprintf is pretty much the only way to do this. My question is, is there anyway to change the output so the text in each column is left justified instead of right justified? My code sample is below where comb is the data frame. TIA, Roger out <- sprintf("%6s %22s %8s %15s

I'm having problems with GPO in Samba 4.2.1 I created a GPO to Block Control Panel and applied in my Domain OU. In desktop client I typed "gpupdate /force" and appear a success message that to ask reboot my system. After rebuot the GPO don't work. Other GPOs as WSUS update, Wallpaper and others, don't work too. Following is the result of command: GPRESULT /H

if i were to have a block size of 4 people and i want to assign a treatment combination to the entire block, there would be 16 different treatment combinations (TTTT, TTTP, TTPP, PTTP, etc.) i am trying to get all 16 permutations and i am able to use this code below. drugs=c('P','T'); comb=expand.grid(drugs,drugs,drugs,drugs) for a block size of 3 the code would be