similar to: Nested? Two-way ANOVA with repeated measures

Dear list members, I need to create a table from a huge list object, this list consists of matrices of the same size (but with different content). The resulting n tables should contain the same rows from all matrices. For example: n <- 23 x <- array(1:20, dim=c(n,6)) huge.list <- list() for (i in 1:1000) { huge.list[[i]] <- x } # One of 1000 matrices huge.list[[1]][1:4, 1:6]

Hi, I want to make a barplot with the following datasets: I have a file as following: name chr position A1 A2 pop1 pop1 pop2 pop2 I have calculated a measure using all the values in columns "pops", the values are saved in a vector. Now I want to make a barplot using the values in this vector as the y axis and the values in the column "position" in the x-axis. thank you

Dear list, I have data like this: dat1 <- data.frame(subject=rep(1:10,2), cond1=rep(c("A","B"),each=5), cond2=rep(c("C","D"),each=10), choice=sample(0:1,10,replace=TRUE)) I would like to compare subjects' "choice" for (cond1=="A" & cond2=="C") vs

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {

Hi, I'm doing a function that describe two populations in competition. that's the function that i wrote: exclusao<-function(n10, n20, k1, k2, alfa, beta, t){ n1<-k1-(alfa*n20) n2<-k2-(beta*n10) if(t==0){plot(t, n10, type='b', xlim=range(c(1:t),c (1:t)), ylim=range(n10, n20), xlab='tempo', ylab='tamanho populacional') points(t, n20, type='b',

Dear R-Users, I would like to know whether it is possible to draw several stacked barplots (i.e. side by side on the same sheet)... my data look like : Cond1 Cond1' Cond2 Cond2' Compartment 1 11,81 2,05 12,49 0,70 Compartment 2 10,51 1,98 13,56 0,85 Compartment 3 1,95 0,63 2,81 0,22 Compartment 4 2,08 0,17

Dear UseRs, I wrote following function in order to solve Data Envelopment Analysis. Reason for posting is that the function is slow when nrow(dat) is large. I wonder if other functions could substitute the for() loop in the code, such as mapply(). Can anybody help to rewrite the dea() function as efficiently as possible? The code is as follows:

summary: Specifically, how does one do stack/FIFO operations in R? Generally, how does one code functions with side effects in R? details: I have been a coder for years, mostly using C-like semantics (e.g., Java). I am now trying to become a scientist, and to use R, but I don't yet have the sense of "good R" and R idiom (i.e., expressions that are to R what (e.g.) the Schwartzian

I am evaluating a switch from Stata to R. I don't need to extensive Statistical methods, but the main reason I am exploring the switch is the coding flexibility in R (e.g. Stata does not support linear/quadratic programming). I have been going over the R syntax and I had a quick question: In Stata, one has a very useful construction called "by", e.g. by month signal: gen xxx =

Thanks. That works great! > df <- data.frame(x=c(1,1,NA,NA,2), y=c('a','a','a','b','b'), z=c(TRUE,FALSE,TRUE,FALSE,TRUE)) > cond1 <- 'x==1' > cond2 <- 'x==1 & z' > df x y z 1 1 a TRUE 2 1 a FALSE 3 NA a TRUE 4 NA b FALSE 5 2 b TRUE > subset(df, subset = ifelse(is.na(eval(parse(text=cond1))), TRUE,

Community, (Windows Xp , 1.7.1, too little memory) This may have the flavor of an answer in search of a question, but I'll pose this question: Is their a better way to do the following than what I'll show below? Problem: In Sweave I have multiple figures from lattice, some of which have more that one page. I can easily figure out the total number of figures I have created, but its

Hi all, suppose there is a vector y with rownames: > y cond1 cond2 cond3 cond4 78.952 87.308 86.490 74.040 how can I easily plot this vector using the rownames? plot(y) gives me a plot with a x-axis from 1 to 4 in 0.5 steps, also plot(rownames(y), y) and plot(y ~ rownames(y) don't work. I know I can build a x-axis with axis(1, ...), but in this case I need a character string like

Hi, I have a general question on LoopUnswtich pass. Consider the following IR snippet: define i32 @test(i1 %cond) { br label %loop_begin loop_begin: br i1 %cond, label %loop_body, label %loop_exit loop_body: br label %do_something do_something: call void @some_func() noreturn nounwind br label %loop_begin loop_exit: ret i32 0 } declare void @some_func() noreturn After running

Hello, I'm trying to build a frequency table for a vector, broken down by the combination of factors. For further analyses, I need to have the result arranged in a new data frame, with the upper limit of the histogram's breaks, the per bin count, and the factors identifying each record. My problem is including the latter: ---<---------------cut

Hi people, I have made some progress trying to work out how to solve this problem but I have got a bit stuck - sorry if this turns out to be a simple exercise . . Allelic Differentiation (AD) in genetics measures the number of different alleles between (say) two populations eg: Organisms in Pop 1 have alleles: a, b, c, d, e Organisms in Pop 2 have alleles: b, b, c, d, e Different

Hello everyone, I am working for a few days already on a basic algorithm, very common in applied agronomy, that aims to determine the degree-days necessary for a given individual to reach a given growth stade. The algorithm (and context) is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and so I implemented my function in R as follows: DD <- function(Tmin, Tmax, Tseuil,

Dear R user: I am studying the allele data of two populations. the following is the data: a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 a16 a17 pop1 0.0217 0.0000 0.0109 0.0435 0.0435 0.0000 0.0109 0.0543 0.1739 0.0761 0.1413 0.1522 0.1087 0.0870 0.0435 0.0217 0.0109 pop2 0.0213 0.0213 0.0000 0.0000 0.0000 0.0426 0.1702 0.2128 0.1596 0.1809 0.0957 0.0745 0.0106

Hi: I have a large dataset mydata, of 1000 rows and 1000 columns. The rows have gene names and columns have condition names (cond1, cond2, cond3, etc). mydata<- read.table(file="c:/file1.mtx", header=TRUE, sep="") I applied PCA as follows: data_after_pca<- prcomp(mydata, retx=TRUE, center=TRUE, scale.=TRUE); Now i get 1000 PCs and i choose first three PCs and make a

I worked this out over the weekend. I appreciate that using temporary variables would be simpler but I think this makes for quite readable code: # in RProfile.site inplace <- function (f, arg=1) eval.parent(call("<-",substitute(f)[[arg+1]], f),2) # examples in code inplace(foo[bar,baz] *2) # or inplace(paste(foo[bar,baz], 1:10)) # or inplace(sub("blah",

Some InstCombine transforms for select-of-select were added here: https://reviews.llvm.org/rL228409 But Alive says this is more poisonous: Name: selsel %s1 = select i1 %cond1, i8 C1, i8 C2 %s2 = select i1 %cond2, i8 %s1, i8 C2 => %andcond = and i1 %cond1, %cond2 %s2 = select i1 %andcond, i8 C1, i8 C2 http://rise4fun.com/Alive/JT6 Are those transforms legal? -------------- next part