similar to: left-justified fixed-width format

All, Below is an xyplot plot with multiple panels and a title produced via main: library("lattic") data.ex = data.frame(y = rnorm(10), t = rep(1:5, 2), group = rep(c(0,1), each = 5)) xyplot(y ~ t | as.factor(group), data = data.ex, main = list("Put figure caption here xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx want this line left justified" )) I must be mis-interpreting the

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

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

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)

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.

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

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

> 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, ? 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)

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,

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

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

Dear Prof.Thank you for your kind response. I have only used: install.packages("tidyverse") install.packages("meta") install.packages("metafor") library(tidyverse) library(meta) library(metafor)and then,forest.meta(hidemeta, layout="RevMan5", xlab="Proportion", comb.r=T, comb.f=F, xlim = c(0,1), fontsize=10, digits=3)Unfortunately I am not

All, I have a package BondLab, all variables are passed to the models via Cusip objects. ? The only variables input by the user are? settlement date,? price or yield or spread. ? Further price may be passed as 100.125, 100-8 (1/8), or 100-2 (2/64) or 100-2+ (5/128).? Once passed these variables must have a steady state (in decimal). ?After reading the R documentation and Hadley's book I

Hi, > Yes, they both are exactly the same. then I don't know what is going on. I suggest you send a copy of comb.ll to the list so that we can see for ourselves. Ciao, Duncan. > > Regards > > Shahzad > > On Tue, Jun 12, 2012 at 9:38 AM, Duncan Sands<baldrick at free.fr> wrote: >> Hi, is the comb.ll used here: >> >> >>> $ time lli

Sure. The comb.ll and data files are attached and can be invoked as the following $ lli comb.ll data -c Regards Shahzad On Tue, Jun 12, 2012 at 12:28 PM, Duncan Sands <baldrick at free.fr> wrote: > Hi, > > >> Yes, they both are exactly the same. > > > then I don't know what is going on.  I suggest you send a copy of comb.ll to > the > list so that we can

Hi, I have the follow ggplot2 code I am running: ggplot(data=bb.res.math,aes(x=factor(id.bb),y=bb.math.comb,fill=BB)) + geom_bar() + facet_grid(BB~.) + scale_fill_brewer(pal="Set1") + ylab("Average Student Residual (Math)") + xlab("Student ID") The number of unique id.bb is 2207 and so my X-axis has a couple of thousands, indistinguishable tick marks that correspond

All, In the function below I have 24 individuals and 6 calculations per individual. The 6 calculations are collected each time in a 1:24 loop when calculating "delta". I'd like to collect all 144 = 24*6 calculations in one vector ("delta.patient.comb"). The function works as is via indexing, but is there an easier way to collect the measurements via appendinng the 6

Dear Sir or Madam, I am trying to plot forest plot. I extracted odds ratio and their corresponding 95% confidence interval from papers, then I calculated the log(OR) and standard error using the following command OR<-metagen(logOR,selogOR,sm="OR") forest(OR,comb.fixed=TRUE,comb.random=TRUE,digits=2) However, it does not produce a forest plot. Can someone kindly help? Thank

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.