similar to: a faster and shorter way to perform calculations?

Consider a data frame (x) with 2 variables, x1 and x2, having equal values. It looks like: x1 x2 1 1 2 2 3 3 Now, consider a second data frame (xk): xk1 xk2 0.5 0.5 1.0 0.5 1.5 0.5 2.0 0.5 0.5 1 1.0 1 1.5 1 2.0 1 0.5 1.5 1.0 1.5 1.5 1.5 2.0 1.5 0.5 2 1.0 2 1.5 2 2.0 2 I have written code to calculate some differences between these

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

useR's, Consider the variables defined below: yvals <- c(25,30,35) x1 <- c(1,2,3) x2 <- c(3,4,5) x3 <- c(6,7,8) x <- as.data.frame(cbind(x1,x2,x3)) delta <- c(2.5, 1.5, 0.5) h <- delta/2 vars <- 3 xk1 <- seq(min(x1)-0.5, max(x1)+0.5, 0.5) xk2 <- seq(min(x2)-0.5, max(x2)+0.5, 0.5) xk3 <- seq(min(x3)-0.5, max(x3)+0.5, 0.5) xks <- list(xk1,xk2,xk3) xk <-

useR's, Consider some variables and a data frame of points: x1 <- c(1,2,3) x2 <- c(3,4,5) xk1 <- seq(min(x1)-.5, max(x1)+.5,.5) xk2 <- seq(min(x2)-.5, max(x2)+.5,.5) expand.grid(xk1=xk1,xk2=xk2) xk1 xk2 1 0.5 2.5 2 1.0 2.5 3 1.5 2.5 4 2.0 2.5 5 2.5 2.5 6 3.0 2.5 7 3.5 2.5 ... 46 2.0 5.5 47 2.5 5.5 48 3.0 5.5 49 3.5 5.5 I want to restrict the data frame to only contain

useR's, I would like to know if there is a way to avoid using FOR loops to perform the below calculation. Consider the following data: > x [,1] [,2] [,3] [1,] 4 11 1 [2,] 1 9 2 [3,] 7 3 3 [4,] 3 6 4 [5,] 6 8 5 > xk Var1 Var2 Var3 1 -0.25 1.75 0.5 2 0.75 1.75 0.5 3 1.75 1.75 0.5 4 2.75 1.75 0.5 5 3.75 1.75

Dear all, I have discovered that there are many things that I used to do in my GIS which are easily done directly in R, for example calculating interpoint distances using geoR and pick out points inside a polygon using splancs. I now wonder, is there a function to create a line object like a watercourse and then calculate the distances between many points in space and this line? I couldn't

Here is a drop-in replacement for the R incomplete beta function. src/math/pbeta.c It is a slightly modified version of the cephes library one from Netlib. In the few cases I tried it seems to give at least 14 digit agreement with the one in S-PLUS (its hard to get more). I'm not sure what performance is like. I'd like to know if it helps with some of the problems which have been

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

I have the following problem. Consider a `classical' test which works for k .ge. 2 samples. Possible interfaces are e.g. xxx.test(x, g) x ... all data, g ... corresponding groups xxx.test(x1, ..., xk) xxx.test(list(x1, ..., xk)) etc etc. Clearly, the first and the second one are nice, but cannot be combined without making `g' (i.e., `group') a named argument. Hence, in

--xk+LtGr+JJ Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Attached is a conversion script for converting current R doc files to the proposed new format ... I'm not sure if it handles everything correctly, as I made just some random checks. The main purpose for posting the thing to the list is such that those interested can get a look at the new format. Of

Hi everybody, I've been looking for a function that combines all variables from a dataset because I need to do multivariate regression. If we have linear regression with an expression like f(x) = a0 + sum(ai*xi) what I want to do is something like f(x) = a0 + sum(ai*xi) + sum(sum(bij * xi * xj)) + sum(sum(sum(cijk*xi*xj*xk))) + ... So I need a function that combines all the values from

Dear readers of the list, I have a problem a comparison of two data from a vector. The comparison yields FALSE but should be TRUE. I have checked for mode(), length() and attributes(). See the following code (R2.10.0): ----------------------------------------------- # data vector of 66 double data X =

I'm pulling my hair (and there's not much left!) on this one. Basically I'm not getting the same result t when I "step" through the program and evaluate each element separately than when I use the outer() function in the FindLikelihood() function below. Here's the functions: Dk<- function(xk,A,B) { n0 *(A*exp(-0.5*(xk/w)^2) + B) } FindLikelihood <-

Signed-off-by: Scott Seago <sseago at redhat.com> --- AUTHORS | 17 ++++++ README | 10 +++ conf/ovirt-agent | 12 ++++ conf/ovirt-db-omatic | 12 ++++ conf/ovirt-host-browser | 12 ++++

Dear WizaRds, I am struggling with the use of twophase in package survey. My goal is to compute a simple example in two phase sampling: phase 1: I sample n1=1000 circuit boards and find 80 non functional phase 2: Given the n1=1000 sample I sample n2=100 and find 15 non functional. Let's say, phase 2 shows this result together with phase 1: ...................phase1........

Dear all, Is there any method in R to find all possible nonnegative integer solutions to the linear equation with unit coefficients as follow: X1+X2+...+Xk=N Thank you, Amin Zollanvari

Dear all, I have a simple question which I unfortunately do not seem to be able to solve myself. I have a (NxK) matrix and want to generate a new matrix by multiplying each row with itself such that the new matrix has dimension ((N*K)xK) (or better, generate an array with dimension (K,K,N)). I tried apply, but that did not work. Any suggestions? Thanks! Stephan ## Here is a simple

Hello! With this email we release an extension to OpenSSH that was initially developed as project for our studies at the Univerity of Applied Sciences in Hagenberg. First we would like to describe the purpose of using Zero-Knowledge (ZK) for user authentication. Traditional authentication methods like challenge-response with passwords or public keys leak information about the credentials of

Dear R experts, I'm trying to find a code to calculate the p-value from the score test for the logistic regression. My fit is like this: logit=beta0+beta1*x1+beta2*x2 +....+ betak* xk. And my H0 is beta1=beta2=...=betak =0. Any help will be highly appreciated. Thank you! Ying

I checked the R procedure HCLUST (hierarchical clustering) but it looks like it requires a full triangular n x n similarity matrix as input, where n = number of observations. The number of variables is 200. My data set has n = 50,000 observations (keywords), and I use ad-hoc similarity measures, not available in R, to measure keyword similarity. Here, the vast majority of the n x n similarities