similar to: SV4 on R?

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

Does R, or will R, be integrating the changes to the Chambers/Lucent S language under their version 5.0? If not already, then when? John Thaden Little Rock, Arkansas, USA -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"

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"

I'm working on the next version of coxme, one step of which is converting the bdsmatrix library from Splus to R. Actually, it is a conversion from S4 methods as first described in the Green book to S4 methods as they currently exist. Mostly it's going ok, but not entirely. 1. The biggest issue is lack of documentation. The online help pages have not been a help; they keep saying

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)

The coxme package has a ranef() method, as does lme4. I'm having trouble getting them to play together, as shown below. (The particular model in the example isn't defensible, but uses a standard data set.) The problem is that most of the time only one of lme4 or coxme will be loaded, so each needs to define the basic ranef function as well as a method for it. But when loaded together

I can't comment on frailtypack issues, but would like to mention that coxme will handle nested models, contrary to the statement below that "frailtypack is perhaps the only .... for nested survival data". To reprise the original post's model cgd.nfm <- coxme(Surv(Tstart, Tstop, Status) ~ Treatment + (1 | Center/ID), data=cgd.ag) And a note to the poster-- you should

I've converted the bdsmatrix package (used by coxme) to the newer style of S4, and uploaded it. It is in the pkg directory of survival, on r-forge. I'm stuck on something that is almost certainly a namespace issue. I've borrowed liberally from Matrix (a big help) and read the documentation, and just upgraded to 2.8.1 - but still stuck. All the tests work when I run them "by

The survival package uses a generalized cholesky decompostition throughout.? If A is a symmetric matrix A= LDL' where L is lower triangular with 1s on the diagonal, D is diagonal, and D[i,i] =0 if column i of A is redundant.? Being able to read the rank and dependencies directly off of D is very handy. The bdsmatrix package uses the same, but exposes it to the user as gchol and solve

The current coxme code has functions that depend on bdsmatrix and others that depend on Matrix, both those pacakges define S4 methods for diag. When loaded, the message appears: replacing previous import ?diag? when loading ?Matrix? Questions: 1. Do I need to worry about this? If so, what can I do about it? I suppose I could add an importFrom directive, but it will be a pain unless there

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

I have been writing quick and dirty S-plus code for years, but for a recent project I took the plunge, bought Venables and Ripley's S Programming, and implemented a class library using new style classes (in S-Plus 6.0). It worked quite nicely and I am wondering about making more routine use of them. Before I make much more of an investment, I have a few questions, both factual and subjective,

I have been writing quick and dirty S-plus code for years, but for a recent project I took the plunge, bought Venables and Ripley's S Programming, and implemented a class library using new style classes (in S-Plus 6.0). It worked quite nicely and I am wondering about making more routine use of them. Before I make much more of an investment, I have a few questions, both factual and subjective,

I am not in favor of the change, which is a choice of rigor over usability. When I am developing code or functions I agree with this, and I view any warnings from R CMD check about shortened arguments as positive feedback. But 90% of my usage of R is day to day data analysis, interactive, at the keyboard. A lot of data sets that come to me have long variable names. What this change will mean

I am confused when trying the function survfit. my question is: what does the survival curve given by plot.survfit mean? is it the survival curve with different covariates at different points? or just the baseline survival curve? for example, I run the following code and get the survival curve #### library(survival) fit<-coxph(Surv(futime,fustat)~resid.ds+rx+ecog.ps,data=ovarian)

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

Hola, ¿qué tal? Hace poco vi que Google había hecho pública su guía de estilo interna para programar en R: http://google-styleguide.googlecode.com/svn/trunk/google-r-style.html Me tomé la libertad de traducirla: http://datanalytics.com/guia_estilo_r.html Cuanto más pienso en ella, más carencias veo. Escribí sobre ello en mi blog (

Brian Ripley recently replied to a comment of mine by referring to a function 'assignInNamespace', which I had not heard of. Is there a good write up on name spaces in R? There are little tidbits in the manuals on the R site, but I found nothing substative. I'd like to understand these better. Terry Therneau

Question: I am trying to impliment a function in R that we use quite regularly in Splus, and it fails due to a lack of the "terms.inner" function in R. The substitute is? Part question and part soapbox: Why remove terms.inner from R? It's little used, but rather innocuous. Mostly soapbox: I figured it was no big deal, as I originally discovered the use of terms.inner from

When I run R CMD check on the survival package I invariably get a note: ... * checking for file ?survival/DESCRIPTION? ... OK * this is package ?survival? version ?3.2-6? * checking CRAN incoming feasibility ... NOTE Maintainer: ?Terry M Therneau <therneau.terry at mayo.edu>? ... This is sufficient for the auto-check process to return the following failure message: Dear maintainer,