similar to: sweep by levels of a factor

Hi I had a hard-to-find bug in some of my code the other day, which I eventually traced to my misusing of sweep(). I would expect sweep() to give me a warning if the elements don't recycle nicely, but X <- matrix(1:36,6,6) sweep(X,1,1:5,"+") [,1] [,2] [,3] [,4] [,5] [,6] [1,] 2 9 16 23 30 32 [2,] 4 11 18 25 27 34 [3,] 6 13 20 22

Dear Experts, The following is my "Iterator". When I try to write a new function with itel, I got error. This is what I have: > supDist<-function(x,y) return(max(abs(x-y))) > > myIterator <- function(xinit,f,data=NULL,eps=1e-6,itmax=5,verbose=FALSE) { + xold<-xinit + itel<-0 + repeat { + xnew<-f(xold,data) + if (verbose) { + cat( +

Hi everyone, I've been having difficulty writing wrapper functions for some functions where those same functions include other functions with eval() calls where the environment is specified. A very simple example using function lmer from lme4: lmerWrapper <- function(formula, data, family = gaussian, method = c("REML", "ML", "PQL", "Laplace",

Dear all, Assume that I have the following data structure: d <- expand.grid(subj=1:5, time=1:3, treatment=LETTERS[1:3]) d$value <- 10 ^ (as.numeric(d$treatment) + 1) + 10 * d$subj + d$time d$value2 <- 100000 + d$value where d$treatment == "C" stands for my control group. What I want to achieve now is to subtract the values corresponding to d$treatment == "C" from

Folks, I'm doing fine with using orthogonal polynomials in a regression context: # We will deal with noisy data from the d.g.p. y = sin(x) + e x <- seq(0, 3.141592654, length.out=20) y <- sin(x) + 0.1*rnorm(10) d <- lm(y ~ poly(x, 4)) plot(x, y, type="l"); lines(x, d$fitted.values, col="blue") # Fits great! all.equal(as.numeric(d$coefficients[1] + m

For example, subtracting 1:2 from the rows of a two-column matrix: > t(apply(matrix(1:6,ncol=2),MARGIN=1,function(y) y - 1:2)) [,1] [,2] [1,] 0 2 [2,] 1 3 [3,] 2 4 > sweep(matrix(1:6,ncol=2),MARGIN=2,1:2,FUN="-") [,1] [,2] [1,] 0 2 [2,] 1 3 [3,] 2 4 Is there a logic to this difference, or is it just a quirk of the history of these

Given a long zoo matrix, the goal is to "sweep" out a statistic from the entire length of the sequences. longzoomatrix<-zoo(matrix(rnorm(720),ncol=6),as.yearmon(outer(1900,seq(0,length=120)/12,"+"))) cnames<-c(12345,23456,34567,45678,56789,67890) colnames(longzoomatrix)<-cnames longzoomatrix[1:24,] 12345 23456 34567 45678

Hi, I am trying to write a function to automate multiple graph generation. My data looks like: Table of numeric values with the following headers: timeM1 statusM1 xM1 timeM2 statusM2 xM2 timeM3 statusM3 xM3 1 2 3 4 5 6 Where M1,M2, M3 hve no similarity except they have a max string length of 7. Examples are mcw0045, adl0003, lei0101. Now, what I want to do is Function(M1, M2,

Dear list, I was curious how to subtract a vector from matrix? Say, I have mat <- matrix(1:40, nrow=20, ncol=2) x <-c(1,2) I want, x-mat[1,] and x-mat[2,], and so on... Basically, subtract column elements of x against column elements in mat. But x-mat won't do it. Thanks, Mike [[alternative HTML version deleted]]

Hi, I have a data frame containing two columns: x<-as.factor(c('a','a','a','a','a','b','b','b','c','d','d','d')) y<-c(1,3,6,8,12,3,4,7,5,6,7,10) X<-data.frame(x,y) X x y 1 a 1 2 a 3 3 a 6 4 a 8 5 a 12 6 b 3 7 b 4 8 b 7 9 c 5 10 d 6 11 d 7 12 d 10 I would like to

I am having a hard time understanding just what 'sweep' does. The documentation states: Return an array obtained from an input array by sweeping out a summary statistic. So what does it mean "weeping out a summary statistic"? Thank you. Kevin

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

I have a function XOLD() from a nearly verbatim port of legacy FORTRAN in a package. I have remplemented this function as XNEW() using much cleaner native R and built-in functions of R. I have switched the package to the XNEW(), but for historical reasons would like to retain the XOLD() somewhere in the package directory structure. An assertion through a README or other will point to

Dear all, I have several character strings with a high number of different levels. unique(x) gives me values in the range of 100-200. This creates problems as I would like to use them as predictors in a coxph model. I therefore would like to convert each of these strings to a new string (x_new). x_new should be equal to x for the top n categories (i.e. the top n levels with the highest

Hey there, I apologize if this is an irritatingly simple question ... I'm a new user. I can't understand why R flips the sign of all data values when reading in external text files (tab delimited or csv) with the read.delim or read.csv functions. The signs of data values also seem to be flipped after assigning a new data.frame from within R (xnew <-- edit(data.frame()). What am

Hi Jean-Marc and others, I put Speex support in Sweep (a sound editor) yesterday, and had some fun with it :) I'd like to get some feedback before releasing it publically. I'm not really used to speech codecs (I work more with music) but I've been quite impressed at the file size and quality (especially when you hear what I did with some of the sample files ;) I didn't have any

Hi, I have a matrix: mymat <- matrix(runif(10*4), ncol=4) I wish to subtract the column means, down the colums, subtract the row means from the rows and add back the grand mean - all the means should be the means of mymat rather than of the new matrix. How can I do this? Any help much appreciated. Thanks Tom _________________________________________________________________

I'm looking for an R equivalent of Beaton's (1964) Sweep algorithim for partial inversion of a matrix by pivoting. It implemented in SAS/IML as sweep(matrix, indices), described here http://support.sas.com/documentation/cdl/en/imlug/59656/HTML/default/langref_sect266.htm and here for python http://adorio-research.org/wordpress/?p=262 -- Michael Friendly Email: friendly AT yorku

Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y,

there are really two related problems here I have a 2D matrix A <- matrix(1:100,nrow=20,ncol =5) S <- matrix(1:10,nrow=2,ncol =5) #I want to subtract S from A. so that S would be subtracted from the first 2 rows of #A, then the next two rows and so on. #I have a the same problem with a 3D array # where I want to subtract Q for every layer (1-10) in Z # I thought I solved this one