similar to: terms.inner

I quickly recieved several replies to my terms.inner question. To summarize: 1. "It was never in R" Clearly I was mistaken in my assumptions. Since gam used it, and gam was ported, I assumed terms.inner had to have been in R at some point. But that version of gam must never have made it to R. 2. Given #1, it's not too surprising that I didn't (yet) get any answers to the

----- begin included message In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is

In my genridge package, I define a function ridge() for ridge regression, creating objects of class 'ridge' that I intend to enhance. In a documentation example, I want to use some functions from the car package. However, that package requires survival, which also includes a ridge() function, for coxph models. So, once I require(car) my ridge() function is masked, which means I have to

I've added a "backsolve" method to the bdsmatrix library. Per the Extending manual section 7.1 I've also added the following 3 lines along with my setMethod definitions for 2 classes. backsolve <- function(r, ...) UseMethod("backsolve") backsolve.default <- base:::backsolve formals(backsolve.default) <- c(formals(backsolve.default), alist(... = )) I've

This arose when working on an addition to coxph, which has the features that the X matrix never has an intercept column, and we remove strata() terms before computing an X matrix. The surprise: when a terms object is subset the intercept attribute is turned back on. My lines 2 and 3 below were being executed just before a call to model.frame. The simple solution was of course to do them in the

Context: R version 2.7.1 (2008-06-23) I don't know when this was upgraded in the department, I just ran into the aberrent behavior today. Problem: Our group BY CHOICE does not change character variables into factors by default. I can get into a long arguement as to why later, and will give one example of why below. The default behavior of S, Splus and R has been to create

Someone sent me a bug report for survival2.44.1-1 that involves a model with both cluster and offset.? It turns out to be a 3 part issue with [.terms and my own untangle.specials routine.?? I've spent an evening sorting out the details. ? 1. The delete.response() function doesn't remove the response from the dataClasses attribute, which leads to a later failure in [.terms for

I am trying to clear up all the "NOTE"s before a CRAN submission, but am a bit confused about this one.?? What is it complaining about -- that it doesn't like my name? ... * checking for file ?deming/DESCRIPTION? ... OK * this is package ?deming? version ?1.4-1? * checking CRAN incoming feasibility ... [7s/18s] NOTE Maintainer: ?Terry Therneau <therneau.terry at mayo.edu>?

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,

Ben, Looking at your notes, it appears that your solution is to write your own terms() function for lme.? It is easy to verify that the "varnames.fixed" attribute is not returned by the ususal terms function. Then I also need to write my own terms function for the survival and coxme pacakges? Because of the need to treat strata() terms in a special way I manipulate the formula/terms in

I have a suggested addition to termplot. We have a local mod that is used whenever none of the termplot options is quite right. It is used here almost daily for Cox models in order to put the y axis on a risk scale: ---- fit <- coxph(Surv(time, status) ~ ph.ecog + pspline(age), data=lung) zz <- termplot(fit, se=TRUE, plot=FALSE) yy <- zz$age$y + outer(zz$age$se, c(0, -2, 2),

I'd like to get interaction terms in a model to be in another form. Namely, suppose I had variables age and group, the latter a factor with levels A, B, C, with age * group in the model. What I would like are the variables "age:group=A", "age:group=B" and "age:group=C" (and group itself of course). The coefficients of the model will then be the age effect

Hi all, I thought y''all might be interested in seeing a newly released website named Soapbox which was written in Rails. Soapbox features reviews of products, businesses, services, and anything else you can think of written by the people *you* care about. http://soapboxit.com Thanks! Duff OMelia -- Posted via http://www.ruby-forum.com/.

I've created some Splus code for a microarray problem that - needed to be in C, to take advantage of some sparse matrix properties - uses a cholesky decompostion as part of the computation For the cholesky, I used the cholesky2 routine, which is a part of the survival library. It does just what I want and I'm familiar with it (after all, I wrote it). In Splus, this all works

Hello, I'm trying to use coxph() function to fit a very simple Cox proportional hazards regression model (only one covariate) but the parameter space is restricted to an open set (0, 1). Can I still obtain a valid estimate by using coxph function in this scenario? If yes, how? Any suggestion would be greatly appreciated. Thanks!!! [[alternative HTML version deleted]]

I'm working on the next iteration of coxme. (Rather slowly during the summer). This is the most subtle code I've done in S, both mathematically and technically, and seems a perfect vehicle for the "literate programming" paradym of Knuth. The Sweave project is pointed at S output however, not source code. I would appreciate any pointers to an noweb type client that was

The survival package makes significant use of the "specials" argument of terms(), before calling model.frame; it is part of nearly every modeling function. The reason is that strata argments simply have to be handled differently than other things on the right hand side. Likewise for tt() and cluster(), though those are much less frequent. I now get "bug reports" from the

I've moved nlme from Depends to Imports in my coxme package. However, a few of the examples for lmekin use one of the data sets from nlme. This is on purpose, to show how the results are the same and how they differ. If I use data(nlme::ergoStool) the data is not found, data(nlme:::ergoStool) does no better. If I add importFrom(nlme, "ergoStool") the error message is that

Martin, I am aware of --vanilla; I use it myself for some testing. In this case R_LIBS_USER was set externally (part of my login) and does not involve any of the R scripts. That means it is inherited by any subprocess. For example: tmt1495% R --vanilla --no-environ R version 3.3.1 (2016-06-21) -- "Bug in Your Hair" Copyright (C) 2016 The R Foundation for Statistical Computing

This question likely has a 1 line answer, I'm just not seeing it. (2, 3, or 10 lines is fine too.) For a vector I can do group <- match(x, unqiue(x)) to get a vector that labels each element of x. What is an equivalent if x is a data frame? The result does not have to be fast: the data set will have < 100 elements. Since this is inside the survival package, and that package is on