similar to: Second largest element from each matrix row

Dear All, I couple of weeks ago, I’ve asked for a package recommendation for nonlinear optimization. In my problem I have a fairly complicated non-linear objective function subject to one non-linear equality constrain. I’ve been suggested to use the *Rdonlp2* package, but I did not get any results after running the program for 5 hrs. Is it normal to run this type of programs for hours? Also,

Dear experts, I'm attempting to solve a constrained optimization problem using the Rdonlp2 package. I created a Lagrange function (L=f(x)-lambda(g(x)-c)), where x is a vector of 16 parameters. This is what I'm using as objective function in the code below. In addition, I set bounds on these parameters (par.u and par.l). When I run the code, I get the error message shown below. Any idea

Hi, I would like to use sweep to "sweep out" proportions and confidence intervals for an array, however when I supply a function which returns a string (containing something like "9% (3-18%)") I get back a list instead of an array, here is a simplified example: # example showing that sweep does not return an array with same dimensions as STATS as advertised

On Thu, Apr 14, 2011 at 7:02 PM, <rcpp-devel-request at r-forge.wu-wien.ac.at> wrote: > I was able to write a very short C++ function using the Rcpp package > that provided about a 1000-fold increase in speed relative to the best > I could do in R. ?I don't have the script on this computer so I will > post it tomorrow when I am back on the computer at the office. > >

Hi, I'm new in Latex and I'm trying to include an R chart into a Latex document. This is what I'm doing: 1) In R: save the chart as a a Postcript in a folder C:/xxx/Density.eps 2) In Latex (using TexWorks on windows xp) : In the preambule: \documentclass[11pt]{article} \usepackage{graphicx} \begin{document} blah..blah…blah \begin{figure} \centering

Hey fellas: I would like to integrate the following function: integrand <- function (x,t) { exp(-2*t)*(2*t)^x/(10*factorial(x)) } with respect to the t variable, from 0 to 10. The variable x here works as a parameter: I would like to integrate the said function for each value of x in 0,1,..,44. I have tried Vectorize to no avail. Thanks in advance, jose romero

Hi, Maybe I'm missing the point here...but let's suppose you are working with "large" data sets and using functions that take a significant amount of time to run in R. I woulnd't like to run these functions every time I call Sweave("myfile.Rnw") within R. What is the "common" practice to use Sweave in these situations. I would just run the function once,

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Let's say I have the data frame 'dd' below. I'd like to select one column from this data frame (say 'a') and keep its name in the resulting data frame. That can be done as in #2. However, what if I want to make my selection based on a vector of names (and again keep those names in the resulting data frame). My attempt is #4 but doesn't work. dd <- data.frame(a =

I have a data frame with a couple million lines and want to retrieve the largest and second largest values in each row, along with the label of the column these values are in. For example row 1 strongest=-11072 secondstrongest=-11707 strongestantenna=value120 secondstrongantenna=value60 Below is the code I am using and a truncated data.frame. Retrieving the largest value was easy, but I have

Dear List, Several times I use this package I get the error message shown below. When I work out simple examples, it turns out to be fine, but when working with real and moderate size data sets I always get the same error. Do you know what could be the cause of the problem? Error in apply(mod.matrix[, components], 1, prod) : subscript out of bounds Error in

Hi, If I use the eigen() function to find the eigenvalues of a matrix, how can I find the eigenvector corresponding to the largest eigen value? Thanks! [[alternative HTML version deleted]]

Hi, OK, if you try to explicitly make them generic, you are told that they are implicitly already generic: > setGeneric("is.finite", function(from, ...) standardGeneric("is.finite")) Error in setGeneric("is.finite", function(from, ...) standardGeneric("is.finite")) : "is.finite" is a primitive function; methods can be defined, but the

Dear R experts, The lrm function in the Design package can perform penalized (Ridge) logistic regression. It is my understanding that the ridge solutions are not equivalent under scaling of the inputs, so one normally standardizes the inputs. Do you know if input standardization is done internally in lrm or I would have to do it prior to applying this function. Also, as I'm new in R (coming

Hi Chris, Chris Lattner wrote: >> 2) Line 369 of PPCInstrInfo.td, we declare the non-callee saved registers. >> However, Linux and Darwin do not have the same set >> of non-callee saved registers. I don't know how to make the if(isDarwin) test >> in here >> > > Take a look at ARM/ARMRegisterInfo.td for an example of this I tried to define Defs just

Dear users, The company where I work is considering getting a license for Revolution Enterprise - Windows 64-bit. I'll appreciate for those familiar with the product if can share your experiences with it? In particular, how does it compare to the "free" version of R 64-bit? Thanks in advance. Regards, Lars. [[alternative HTML version deleted]]

Hello, This is my first post to the help request list, so I'm going to err on the side of giving too much information. I'm working on writing a simulation in which agents will make repeated production and exchange decisions with randomly chosen partners. The idea is, all agents can produce two goods which they want to consume, they choose a value t in [0,10] which sets their production

What is the most efficient alternative to x[order(x)][1:n] where length(x)>>n? I also need the positions of the mins/maxs perhaps by preserving names. Thanks for any suggestions. -- View this message in context: http://www.nabble.com/Largest-N-Values-Efficiently--tf4788033.html#a13697535 Sent from the R help mailing list archive at Nabble.com.

hI I have to calculate V statistic for each row of a large dataframe (28000). I can not use multtest package for paired wilcox test. I have been using for loop which are. Is there a way to speed the computation with another method like using apply or tapply? My data set looks like this: 11573_MB 11911_MB 11966_MB 12091_MB 12168_MB 12420_MB................ cg00000292

Dear R users, I’ve search the R site for help on this topic but it is hard to find a precise answer for my questions. Which are the best options to overcome the RAM memory limitation problems when using R on “large” data sets (such as 2 or 3 million records)? - Is the free available version of R (as opposed to the one provided by REvolution Computing) compatible with a windows 64-bit