similar to: Package checking: verifying plots

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

You can fit a linear probability model with glm and a bit of arm twisting. First, make your own copy of the binomial function: > dump('binomial', file='mybinom.R') Edit it to change the function name to "mybinom" (or anything else you like), and to add 'identity' to the list of okLinks. Source the file back in, and use mybiom('identity') to fit

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

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,

I used both BMDP and SAS in my earlier years, side by side. At that time the BMDP statistical methods were much more mature and comprehensive: we treated them as the standard when the two packages disagreed. (It was a BMDP manual that clearly explained to me what the hypothesis of "Yate's weighted mean test" is, something SAS decided to call "type III" and eternally

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

>>>>> Fox, John <jfox at mcmaster.ca> >>>>> on Thu, 14 Sep 2017 13:46:44 +0000 writes: > Dear Martin, I made three points which likely got lost > because of the way I presented them: > (1) Singularity is an unusual situation and should be made > more prominent. It typically reflects a problem with the > data or the

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

I've recently updated the coxme package, which calls internal routines from the bdsmatrix package.? (It is in fact mentioned as an example of this in the Extensions manual.) The call connections are a blocks like this, one for each of the 9 called C routines. void bdsmatrix_prod4(int nrow,??? int nblock,?? int *bsize, ??????????????????? double *bmat, double *rmat, ??????????????????? int

Dear Terry, Does fitting group + age:group instead of age*group solves your problem? Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more

Hello, I have some measurements that I am trying to fit a model to. I also have uncertainties for these measurements. Some of the measurements are not well detected, so I'd like to use a limit instead of the actual measurement. (I am always dealing with upper limits, i.e. left censored data.) I have successfully run survreg using the combination of well detected measurements and limits,

Dear R-user: I am using survreg(Surv()) for fitting a Tobit model of left-censored longitudinal data. For logarithmic transformation of y data, I am trying use survreg.distributions in the following way: tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="gaussian", data=y.data, scale=0, weights=w) my.gaussian<-survreg.distributions$gaussian

I have a test directory for the survival suite, and dyn.load has ceased to work in it. Below shows the log: tmt1075% R --vanilla R version 2.12.2 (2011-02-25) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-unknown-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain