similar to: vectorizing problem

Hi, I'm trying to make a boxplot with the data at the end of the message, and when I try to execute the command >boxplot(Diatoms) (or for any other field instead of "Diatoms") I get the following error message: Error in oldClass(stats) <- cl : adding class "factor" to an invalid object Any advice would be much appreciated. Thanks a lot, Miriam Date

Hello, I'm having an issue with one particular server and am hoping someone here has dealt with this. I'm not sure whether this is a strictly samba issue or relates to the way rsync walks the file list. Basically after mounting a Windows 2000 file system using and then rsyncing the contents of this mount, it seems to take 5 - 8 hours to complete. I've checked on the log

Dtrace and Performance Teams, I have the following IO Performance Specific Questions (and I''m already savy with the lockstat and pre-dtrace utilities for performance analysis.. but in need of details regarding specifying IO bottlenecks @ the controller or IO bus..) : **Q.A*> Determining IO Saturation bottlenecks ( */.. beyond service times and kernel contention.. )/ I''m

---------- Forwarded message ---------- From: <r-help-owner@r-project.org> Date: 2013/2/8 Subject: vegdist Error en double(N * (N - 1)/2) : tama?o del vector especificado es muy grande To: caro.bello58@gmail.com Message rejected by filter rule match ---------- Mensaje reenviado ---------- From: caro bello <caro.bello58@gmail.com> To: r-help@r-project.org Cc: Date: Fri, 8 Feb 2013

On Wed, Apr 01, 2020 at 03:33:00PM -0700, Jeremy Allison via samba wrote: > On Wed, Apr 01, 2020 at 02:09:57PM -0700, Alexey A Nikitin via samba wrote: > > Hi, > > > > Recently I by mistake ran `wbinfo -u <username>` when I was actually intending to run `wbinfo -n <username>`. It ignored the <username> part and proceeded to fetch the usernames. On a small

Hello all/Timo, Up until now, my main Clients office has consisted of a single location, and I have never had to deal with the situation of multiple locations for a single company. They have just told me that they are acquiring an additional floor at a building that is about 4 minutes away - but obviously far enough away that I now have to deal with supporting users in the same domain but at

On Feb 5, 2013, at 9:22 AM, Hal Finkel <hfinkel at anl.gov> wrote: > I think that the potential for overlap is indeed there, but don't we already insert runtime overlap checks as necessary? This seems like it would just be another such case. We insert runtime overlap checks only for unidentified objects. The problem here is that the vectorizer thinks that A,B,C are all pointers to

The original problem I posed was Let x = real vector of length n y = real vector of length n w = real vector of length m, m typically less than n/2 but can be > n z = real vector of length m For w[i], i=1,,,m, find the value of x that is closest to w[i]. In the case of ties, select one (optimally at random or just take the first match). Let z[i] = value of y corresponding to the

Hello everybody. I have a dozen or so vectors (of different lengths) which I want to coalesce into a dataframe, as in the following toy example. R> foo <- c(1,2,3) R> bar <- c(7,8) R> data.frame(name =c(rep("foo",length(foo)),rep("bar",length(bar))), value=c(foo,bar)) name value 1 foo 1 2 foo 2 3 foo 3 4 bar 7 5 bar

Dear r-helpers, I am developing a smoothing function that performs a casewise deletion of all the non-informative observations in a bivariate dataset following the Poisson - D'Avril algorythm. But I am now facing two problems: 1)Being based on loops, the function takes a lot of time before having done its work and even if I tried I was not able to vectorize it. 2) I cannot control the

Dear R-helpers, I have two problems that I don't know how to vectorize (but would like to because my current solution is slow). # 1. #I have a vector x: x <- c(3, 0, 1, 0, 2, 2, 2, 0, 4, 2) #I want this translated into a new vector based on x,so that each element of x #is the number of zeroes, followed by a 1. The new vector would look like: #> r# [1] 0 0 0 1 1 0 1 1 0 0 1 0 0

Hello, I have to build a function that takes a time serie and calculate the momentum. For each date of the serie, I have to build a loop to calculate it using the last few data. My problem is that it takes one minute to compute and I need to run this function very often. I would like to vectorize it, as much as possible. Can somebody help me? I have read the

Hi, I'm a newbie when it comes to R, and I'm trying to figure out how to use vectorization as opposed to for loops. In particular, how can I create a function that is applied on each element of a row, but can access previous elements relative to that element? My problem: I want to calculate something like x[i] = x[i] / x[i - 1] for each element of a vector x: ex. x <- data.frame(a

Hi All, I am trying to convert the following piece of matlab code to R: XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1); #square the elements of X1, weight it and repeat this vector N1 times XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1); #square the elements of X2, weigh and repeat this vector N2 times X1X2 = (w(:,ones(1,N1)).*X1)'*X2; #get the weighted 'covariance'

So I have a problem that I'm trying to get through, and I just can't seem to get it to run very fast in R. What I'm trying to do is to find in a vector a local peak, then the next time that value is crossed later. I don't care about peaks that may be lower than this first one - they can be ignored. I've tried some sapply methods along the way, but they all are slower.

I have written a program to solve a particular logistic regression problem using IRLS. In one step, I need to integrate something out of the linear predictor. The way I'm doing it now is within a loop and it is as you would expect slow to process, especially inside an iterative algorithm. I'm hoping there is a way this can be vectorized, but I have not found it so far. The portion of code

On 5 February 2013 17:28, Nadav Rotem <nrotem at apple.com> wrote: > We insert runtime overlap checks only for unidentified objects. The > problem here is that the vectorizer thinks that A,B,C are all pointers to > the same array, so it gives up. If A,B,C were different arrays then it > could have used runtime checks. > Yes, that is exactly the code that creates the

Sorry, if this question is rather basic, but being a newbie I still have problems to think in the "R way". My problem is as follows: - I have a data frame X with stock prices X$Price and corresponding dates X$Date. - Now I want to get for each date x in X$Date the index z, such that z = min (a | X$Date(a)>x and X$Price(a)>Price(x) To put it simple, I am looking for the

On Oct 24, 2013, at 3:00 PM, Chandler Carruth <chandlerc at google.com> wrote: > Just a note, I don't think you should or need to vectorize the actual alloca stuff. If you can simply transform the dynamically indexed load: > > Then running SROA and InstCombine will mop up the rest. So its mostly about getting the SLPVectorizer to handle the dynamic GEP. As soon as it does

Dear R users I have a 4-dimensional matrix (actually several 3d (x,y, slices) matrices appended over time (volumes)) say, e.g. I want to z-transform the data (subtract the mean and divide by the std-deviation) for (slice in 1:slices) { for (x in 1:x.dim) { for (y in 1:y.dim) { t <- as.matrix(my.matrix[x,y,slice,1:volumes]) for (vol in 1:volumes) {