similar to: browser() exits when not desired, in three different scenarios (PR#11623)

Tim, I have reported some similar issues a while back and there was some discussion on this topic: http://tolstoy.newcastle.edu.au/R/devel/06/03/4609.html Good luck, Kevin On Tue, Jun 10, 2008 at 6:47 PM, Tim Hesterberg <timhesterberg at gmail.com> wrote: > Here are three different scenarios in which the browser() exits > when I don't want it to. These are all related to the

>>>>> "BDR" == Prof Brian Ripley <ripley at stats.ox.ac.uk> >>>>> on Fri, 30 May 2008 22:34:28 +0100 (BST) writes: BDR> I think it is ESS that is parsing this as a help BDR> request (so it can divert it to an ESS buffer). BDR> Looks like this is an ESS issue, not an R one. yes, indeed, hence much more belonging the ESS-help

> ?agrep > Results in: No documentation for 'agrep ' in specified packages and libraries: you could try 'help.search("agrep ")' There is white space after agrep, that ? doesn't ignore. --please do not edit the information below-- Version: platform = i486-pc-linux-gnu arch = i486 os = linux-gnu system = i486, linux-gnu status = major = 2 minor =

If save() fails because an object is not found, it should not overwrite an existing file. > a <- 1:9 > save(a, file = "a.rda") > rm(a) > load("a.rda") > a [1] 1 2 3 4 5 6 7 8 9 > rm(a) > save(a, file = "a.rda") Error in save(a, file = "a.rda") : object 'a' not found > load("a.rda") Error in

I've run into a scoping problem in R. I'm calling a function that * creates a formula * calculates a weight vector * calls lm with that formula and weights This fails. Here's a simplified reproduce example: # f works, g doesn't, h is a workaround rm(w) data <- data.frame(y=runif(20), x=runif(20), z=runif(20)) f <- function(k){ w <- data$z^k coef(lm(y~x, data

On 5/30/2008 11:40 AM, rocket at google.com wrote: > I've run into a scoping problem in R. No, in your use of it. > I'm calling a function that > * creates a formula ... incorrectly. > * calculates a weight vector > * calls lm with that formula and weights > This fails. > > Here's a simplified reproduce example: > # f works, g doesn't, h is

I would like a way to modify the behavior of browser(), so that entering a blank line does nothing rather than being equivalent to "c". I'm running R using emacs ESS. I often debug functions by inserting a browser, and stepping through one line at a time, sending a line at a time from a buffer with the function to the R buffer. But every time I send a blank line, the browser

I'm trying: R CMD Rdconv file.Rd --type=Ssgm If file.Rd contains \code{x} then this is currently translated as <s-expression>x</s-expression> I suggest instead translating to <code>x</code> (provided that R CMD Sd2Rd is changed to support the <code> tag; I just submitted that bug separately). Note that this is an enhancement, not a bug. This change would

A new 'dataframe' package is on CRAN. This is a modified version of the data frame code in R, modified to make fewer copies of the inputs and run faster, e.g. as.data.frame(a vector) makes 1 copy of the vector rather than 3, data.frame(a vector) makes 3 copies rather than 6, and x[, "a"] <- newValue makes (2,2,1) copies of (old data frame, new column, integer vector of

Full_Name: Benny van der Vijgh Version: 2.7.2 OS: Windows Vista Submission from: (NULL) (194.171.252.108) The return value of peaks() in package splus2R is not consistent. This is because of the call to max.col() without additional parameters which peaks() makes. max.col() has a parameter 'ties.method' which specifies how ties are handled, with "random" by default. This means

Dear R-friends I have three matrices e.g. var <- matrix(c(4,4,4,4,0,4,4,4,0,3,3,0),nrow=4); val <- matrix(c(0.6,0.6,0.6,0.6,0,1.6,1.6,1.6,0,4.9,4.9,0),nrow=4); nod <- matrix(c(-1,-1,1,1),ncol=1) > var [,1] [,2] [,3] [1,] 4 0 0 [2,] 4 4 3 [3,] 4 4 3 [4,] 4 4 0 > val [,1] [,2] [,3] [1,] 0.6 0.0 0.0 [2,] 0.6 1.6 4.9 [3,] 0.6 1.6

Dear All, For function: rmvnorm{mvtnorm} in (library mvtnorm, not splus2R), if I generate 2 bivariate normal samples as follows: > rmvnorm(2,mean=rep(0,2),sigma=diag(2)) [,1] [,2] [1,] 2.0749459 1.4932752 [2,] -0.9886333 0.3832266 Where is the first sample, it is stored in the first row or the first column? Does this function store samples row-wise or column-wise? Thank

Scenario 1: Package-centric Have the .deb package for NUT install a single-user/single-UPS configuration, with the .deb asking for the UPS type and dispatching on that to set up ups.conf for the correct driver. Package installation could even create a nut user and group, so there wouldn't even be a security compromise. I don't know how to do the equivalent with RPM, because RPM

Hi, consider this one as an FYI, or a seed for further discussion. I am aware that many traps on sample() have been reported over the years. I know that these are also documents in help("sample"). Still I got bitten by this while writing sample(units, size=length(units)); where 'units' is an index (positive integer) vector. It works in all cases as expected (=I expect)

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Insightful is seeking a pre-doctoral student and an undergraduate student for two internship positions. The primary responsibilities are to assist in the development of software for high-dimensional regression and machine learning applications using least angle regression (LARS). The pre-doctoral candidate should have a background and interest in statistical methodology, algorithms, data

Below is a version of [.data.frame that is faster for subscripting rows of large data frames; it avoids calling duplicated(rows) if there is no need to check for duplicate row names, when: i is logical attr(x, "dup.row.names") is not NULL (S+ compatibility) i is numeric and negative i is strictly increasing "[.data.frame" <- function (x, i, j,

Hi R-fellows, I am trying to simulate a multivariate correlated sample via the Gaussian copula method. One variable is a binary variable, that should be autocorrelated. The autocorrelation should be rho = 0.2. Furthermore, the overall probability to get either outcome of the binary variable should be 0.5. Below you can see the R code (I use for simplicity a diagonal matrix in rmvnorm even if it

I suggest a simple enhancement to segments() and arrows() to facilitate drawing horizontal and vertical segments -- set default values for the second x and y arguments equal to the first set. This is handy, especially when the expressions for coordinates are long. Compare: Segments: < function (x0, y0, x1 = x0, y1 = y0, col = par("fg"), lty = par("lty"), --- > function

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to