similar to: S v. 5

Peter Dalgaard BSA <p.dalgaard at biostat.ku.dk> wrote: > Martin Maechler <maechler at stat.math.ethz.ch> writes: [ snip... ] > > >From this logic, coercing to a matrix should coerce to character rather > > than integer/numeric codes. > > Hm. I'm not sure there really is much logic in this... Factors are > sometimes character-like, sometimes

Dear R-Developers, The traffic today on s-news where Terry Therneau, I, and others are reporting some of the problems we have had using or converting applications to SV4 reminded me of something Duncan Temple Lang had mentioned to me a year ago that I wanted to follow up on. I recall that Duncan said either that if SV4 were to be implemented in R that it would not be the default behavior, or

Dear Martin, Since no one else has picked up on this, I?ll take a crack at it: The proposal is to define the S3 class of model-frame objects as c(?model.frame?, ?data.frame?) (not the formal class of these objects, even though this feature was coincidentally introduced in S4). That?s unlikely to do harm, since model frames would still ?inherit? data.frame methods. It's possible that some

I use the step() function occasionally, and I think I understand its objective, proper use, and limitations. Now I see stepwise model selection being used in what seems to be an unusual way, and I wonder if it is right or wrong. May I describe? Genetic mapping tries to find where in an animal's genome are genetic elements that influence a particular physical trait. Say there are 100

Hi all, Please help Ive been wasting days at this... I am not trying to create a PDC, I am not joining an active directory, I am not needing samba schema in my openldap (or do I?), I am not trying to use winbind and idmaps for translations from SID to UID/GID, I just want my samba server which shares linux home directories to authenticate user+password against my existing linux based openldap

R pattern-matching and replacement functions are vectorized: they can operate on vectors of targets. However, they can only use one pattern and replacement. Here is code to apply a different pattern and replacement for every target. My question: can it be done better? sub2 <- function(pattern, replacement, x) { len <- length(x) if (length(pattern) == 1) pattern <-

Dear R-helpers: My question is how do I efficient and valid correct for multiple tests in a repeated measurement design: Suppose we measure at two distinct visits with repeated subjects a treatment difference on the same variable. The treatment differences are assessed with a mixed model and adjusted by two methods for multiple tests: # 1. Method: Adjustment with library(multcomp)

Hi all, Was wondering if any body would know if the book "Programming with Data" a guide to S language could be used as a guide to working with the R language. Comments, suggestions, a book review is welcomed. Thanks Josef Bohart -------------- next part -------------- An HTML attachment was scrubbed... URL:

When formula() is applied to the output of model.frame() it ignores the formula in the model.frame's 'terms' attribute: > d <- data.frame(A=log(1:6), B=LETTERS[rep(1:2,c(2,4))], C=1/(1:6), D=rep(letters[25:26],c(4,2)), Y=1:6) > m0 <- model.frame(data=d, Y ~ A:B) > formula(m0) Y ~ A + B > `attributes<-`(terms(m0), value=NULL) Y ~ A:B This is in part

Dear R-Help list: I'm using the Matrix library to operate on 600 X ~5000 element unsymmetrical sparse arrays. So far, so good, but if I find I need more speed or functionality, how hard would it be to utilize other sparse matrix toolsets from within R, say MUMPS, PARDISO or UMFPACK, that do not have explicit R interfaces? More information on these is available here

I found that predict.gnls failed with a wierd error message about a non-numeric argument to a binary vector in one of three nearly identical uses. Error in Inh/Ki : non-numeric argument to binary operator (Inh and Ki are arguments to the function used in the formula for the object whose predictions were requested). It turns out that the problem is in getCovariateFormula(). The final line in

Hello, The code below is supposed to be a wrapper for matplot to do columnwise visible comparison of several matrices, but I'm doing something wrong because I can't access an argument called 'colnum'. I'd be most grateful for some insight. Thanks, John Thaden Little Rock, AR ################################ # mmatplot is a matplot wrapper to compare the same column of #

This shouldn't be hard, but it's just not coming to me: Given a vector, e.g., v <- c(20, 134, 45, 20, 24, 500, 20, 20, 20) how can I get the index of the last value in the vector having a value greater than n, in this case, greater than 20? I'm looking for an efficient function I can use on very large matrices, as the FUN argument in the apply() command. Confidentiality

At 03:28 30/04/97, ihaka at stat.auckland.ac.nz wrote: >Bill Venables writes: > (As a complete side-issue, Brian Ripley and I have a kind of > convention: we refer to the language as "S" and the commercial > product as "S-PLUS". There is a useful distinction to be made.) > >This is generally what I try to do too. > >However, I suspect though that most

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

I am pretty pleased with baselines I fit to chromatograms using the runquantile() function in caTools(v1.6) when its probs parameter is set to 0.2 and its k parameter to ~1/20th of n (e.g., k ~ 225 for n ~ 4500, where n is time series length). This ignores occasional low- side outliers, and, after baseline subtraction, I can re-adjust any negative values to zero. But runquantile's

I don't have a copy of SV4 (or SV3, where model.frame was introduced), but S+ 8.3 (based on SV4) puts the class "model.frame" on model.frame()'s return value but has no methods (in the default packages) for class "model.frame". Perhaps that is why R omitted the class. However, S+ 8.3's (and problably S's) formula.data.frame did look for a "terms"

Hello all, How do I actually use the output of predict.lm(..., type="terms") to predict new term values from new response values? I'm a chromatographer trying to use R (2.15.1) for one of the most common calculations in that business: - Given several chromatographic peak areas measured for control samples containing a molecule at known (increasing) concentrations, first

Martyn Plummer writes: > How important is it to avoid being sued, or less facetiously, what is > the legal status of R? If I were Mathsoft I would be less than pleased > at the development of R and would try to stop it if I could. I have > been wondering for some time if this is possible. But I am not a lawyer > and the issue seems very unclear to me. To me too (Robert spent a