similar to: How do I generate multiple (similar) objects within R?

Hi everybody, I am currently working on mixtures of two densities ( f(xi,teta)= (1-teta)*f1(xi) + teta*f2(xi) ), particularly on the behavior of the variance for teta=0 (so sample only comes from the first distribution). To determine the maximum likelihood estimator I use the Newton-Rapdon Iteration. But when computing the first derivative I get a none linear function (with several asymptotes)

Dear R helpers Suppose I have a vector as vect1 = as.character(c("ABC", "XYZ", "LMN", "DEF")) > vect1 [1] "ABC" "XYZ" "LMN" "DEF" I want to reverse the order of this vector as vect2 = c("DEF", "LMN", "XYZ", "ABC") Kindly guide Regards Vincy [[alternative HTML

HI, R user, I generate the vectors with the same length. I want to put each vector into each column of data frame. Why it doesnt work`? rm<-data.frame() for(a in 1:6){ rm[,a]<-getmeasure(p1,a,speech) } thanks a lot Tammy _________________________________________________________________ Share your memories online with anyone you want.

Hi R users: I have de following data frame (called "Sx") Descripcion Nitratos Cont85g 72.40 Cont85g 100.50 Cont85g 138.30 Cont80g 178.33 Cont80g 79.01 Cont80g 74.16 Cont75g 23.70 Cont75g 15.80 Cont75g 16.20 Patron80g

Dear R helpers Suppose I have a vector as vect_1 = c("AAA", "AA", "A", "BBB", "BB", "B", "CCC") vect_1_id = c(1:length(vect_1)) Through some process I obtain vect_2_id = c(2, 3, 7), then I need a new vector say vect_2 which will give me vect2 = ("AA", "A", "CCC")  i.e. I need the subset of

I have a set of character vectors of uneven length that I have stored in a list. I can easily enough get any column of them using lapply but what I want is to be able to create a matrix of them. Other than some kind of brute force looping approach I have drawn a blank. Would somebody please suggest something? Thanks Example. mylist <- list(aa=c("cat","peach" ),

Hello, i would like to ask you another question. Is exist anymethod to vectors that tells me the last element?That is to say,I have a vector, I want to return the position of last element. I hope having explained. A greeting, Ignacio. -- View this message in context: http://old.nabble.com/Method-tp26493442p26493442.html Sent from the R help mailing list archive at Nabble.com.

Hi ? This is giving me a headache. I?m trying to do a relatively simple optimization ? actually trying to approximate the output from the Excel Solver function but at roughly 1000x the speed. ? The optimization parameters look like this. The only trouble is that I want to add a constraint that sum(wgt.vect)=1, and I can?t figure out how to do that in optim. Mo.vect <-

Hello, I have a question regarding subsetting of vectors. Here's an example of what I'm trying to do: vect.1 <- c(76,195, 290, 380) vect.2 <- c(63, 95, 133, 170, 215, 253, 285, 299, 325, 375) I would like to subset vect.2 so that it has the same length as vect.1, and its numbers are the first corresponging higher value compared to vect.1. The output should be: final.output =

Hi, I got caught out by this behaviour in 1.8.0 and I wondered why this happens: I have a list of vectors and was using lapply and grep to remove matched elements that occur in only a subset of the elements of the list: locs <- lapply(locs, function(x){x[- grep("^x", x)]}) The problem is that where the grep finds no matches and hence returns a vector of length 0, all the

The subject says it all: Has anyone had any experience with using globalize and acts_as_versioned (or equivalent) together. That is, I would like the version control to take the locales into account, the en-US translation could be on version 7 while the fr-FR version is 3. Am thinking about extending these plugins but maybe someone has already done this? Tanks in advance. Regards Erik Lindblad

Thanks Bert. But everyone on that forum wants to use finance tools rather than general optimization stuff! And I am not optimizing a traditional Markowitz mean-variance problem. Plus, smarter people here. :-) > On May 3, 2018, at 3:01 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > You can't -- at least as I read the docs for ?optim (but I'm pretty > ignorant

Thanks a lot to Demitris for a prompt answer some minutes ago on another tread (see below). To avoid excess mails on the list, I move onto next question: I have another small plotting problem that confuses me. I want to plot results from a field trial series, using the numbers of the trials as symbols in the plot. pch = as.character(trial_no) works fine, but truncates the trial number to the

Hi there, I have a numeric vector let say: Vect <- c(12.234, 234.5675, 1.5) Now I want a string vector like: changedVec <- c("012.234", "234.568", "001.500") Would be grateful if somebody help me how can I do that. Thanks and regards, [[alternative HTML version deleted]]

Folks; I am having a problem with the cv.glm and would appreciate someone shedding some light here. It seems obvious but I cannot get it. I did read the manual, but I could not get more insight. This is a database containing 3363 records and I am trying a cross-validation to understand the process. When using the cv.glm, code below, I get mean of perr1 of 0.2336 and SD of 0.000139. When using a

I'm trying to use Rprof() to identify bottlenecks and speed up a particullary slow section of code which reads in a portion of a tif file and compares each of the values to values of predictors used for model fitting. I've written up an example that anyone can run. Generally temp would be a section of a tif read into a data.frame and used later for other processing. The first portion

Hi All, I want to draw samples (n=4) from one of 2 triangular distributions for each value in a matrix. I am using an ifelse statement to try to define which distribution to draw from. >From the output, I can see that the ifelse statement is choosing the correct distribution, however, my n=4 simulations aren't occurring. Is there a way to adjust the ifelse statement to fix this, or must

On Thu, May 3, 2018 at 2:03 PM, Michael Ashton <m.ashton at enduringinvestments.com> wrote: > Thanks Bert. But everyone on that forum wants to use finance tools rather than general optimization stuff! And I am not optimizing a traditional Markowitz mean-variance problem. Plus, smarter people here. :-) > I'm very confused by these statements. Most of the "finance tools"

Hi, I was trying to get error bars in my matplot. I looked at an earlier thread, and the sample code that I made is: #------------------ library(plotrix) mat1 <- matrix(sample(1:30,10),nrow=5,ncol=2) ses <- matrix(sample(1:3,10,replace=T),nrow=5,ncol=2) vect <- seq(20,100,20) rownames(mat1) <- rownames(ses) <- vect colnames(mat1) <- colnames(ses) <- letters[1:2]

Hi Michael, A few comments 1. To add the constraint sum(wgt.vect=1) you would use the method of Lagrange multipliers. What this means is that in addition to the w_i (the components of the weight variables) you would add an additional variable, call it lambda. Then you would modify your optim.fun() function to add the term lambda * (sum(wgt.vect - 1) 2. Are you sure that you have defined