similar to: Potential bug in update.formula when updating offsets

Terry, Martin Would this happen to be related to the "indexing term objects" issue that has been bothering you? -pd > On 5 Aug 2019, at 21:44 , Paul Buerkner <paul.buerkner at gmail.com> wrote: > > Hi all, > > update.formula does not seem to correctly update (i.e. remove in my case) > offset terms. > > Here is an example: > > update(~x +

>>>>> Duncan Murdoch >>>>> on Fri, 5 Apr 2019 11:12:48 -0400 writes: > On 05/04/2019 10:46 a.m., Therneau, Terry M., Ph.D. wrote: >> >> >> On 4/5/19 9:39 AM, Duncan Murdoch wrote: >>> On 05/04/2019 10:19 a.m., Therneau, Terry M., Ph.D. wrote: >>>> Duncan, >>>> ?? I should have

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 recently had a long argument wrt the survival package, namely that the following code didn't do what they expected, and so they reported it as a bug ? survival::coxph( survival::Surv(time, status) ~ age + sex + survival::strata(inst), data=lung) a. The Google R style guide? recommends that one put :: everywhere b. This breaks the recognition of cluster as a "special" in the

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

Hi, I add a div to my document and use an effect to make it apear gracefully. Unfortunatly, when adding the element, the element apears shortly, then the effect (slideDown) lets it apear nicely - so the page flickers abit - What is the best practice to avoid it? Cheers, Ron

Dear List I have experienced that objects generated with one of my packages used a lot of space when saved on disc (object.size did not show this!). some debugging revealed that formula and call objects carried the full environment of subroutines along, including even stuff not needed by the formula or call. here is a sketch of the problem ,---- | test <- function(x){ | x <-

Howdy, I'm looking for a way to restrict which ssh keys are forwarded to a given remote host because we have several ssh domains. That is, I have two keys which I use throughout the day: .ssh/network-a-2014-10-12 .ssh/network-b-2014-11-22 I need to forward my network A key to the ssh gateway host for Network A to allow me to log into hosts on the other side of the gateway but I

I want use survfit() and basehaz() inside a function, but it doesn't work. Could you take a look at this problem. Thanks for your help. Following is my codes: library(survival) n <- 50 # total sample size nclust <- 5 # number of clusters clusters <- rep(1:nclust,each=n/nclust) beta0 <- c(1,2) set.seed(13) #generate phmm data set Z <- cbind(Z1=sample(0:1,n,replace=TRUE),

Hi I wonder if you can help me. I'm currently studying Networking as a college course and one of the challenges we have been set is to research, then put into practice the mapping of a linux server onto a Windows NT server. I'll be honest with you, I'm very new to all this so I hope I explain this correctly. I have successfully created my own smb.conf file, usernames, areas and a

Dear list, I am not familiar with survival analysis and I would need your help to understand a result I have obtained. I have used the following command line to look at number of events and probability of survival at the first 5 years: > su = summary(survfit(Surv(a[, Date], a[, Event]) ~ strata(a[,Prediction]), data = a), times=c(0,1,2,3,4,5)) I have studied two kind of events (disease-free

Dear all, I'm updating a package regarding a new type of models, and I'm looking to extend the formula interface with two functions (L() and R() ) for construction of these models. I want to use as much of the formula interface as possible, and hoped to do something similarly to I(). I know the I() function does nothing more than add the class "AsIs". I've been browsing the

This arose in testing [.terms and has me confused. data(esoph)?? # use a standard data set t0x <- terms(model.frame( ~ tobgp, data=esoph)) t1 <-? terms(model.frame(ncases ~ agegp + tobgp, data=esoph)) t1x <- (delete.response(t1))[-1] > all.equal(t0x, t1x) [1] TRUE # the above is wrong, because they actually are not the same > all.equal(attr(t0x, 'dataClasses'),

A user sent me an example where coxph fails, and the root of the failure is a case where names(mf) is not equal to the term.labels attribute of the formula -- the latter has an extraneous newline. Here is an example that does not use the survival library. # first create a data set with many long names n <- 30? # number of rows for the dummy data set vname <- vector("character",

dear all, Is the following intentional? Am I missing anything in documentation? d<-data.frame(y=rnorm(10,5,.5),exp=rnorm(10), age=rnorm(10)) formula(lm(exp(y)~exp+age, data=d)) #--> exp(y) ~ exp + age formula(lm(exp(y)~., data=d)) #--> exp(y) ~ age variable 'exp' (maybe indicating "experience") is not included in the model. The same happens with 'log' (and

In the code for 'aggregate.formula', there is if (as.character(formula[[2L]] == ".")) I believe that it is meant to be if (as.character(formula[[2L]]) == ".") However, if (as.character(formula[[2L]] == ".")) gives the expected result. Tracing: - formula[[2L]] == "." is equivalent to as.character(formula[[2L]]) == "." From the help page for

I recently got a request to add head() and tail() methods for Surv objects, which is quite reasonable, but not unlike other requests for logLik,? vcov, extractAIC, ...?? What they all have in common is that are methods added since creation of the survival package, and that I didn't know they existed. To try and get ahead of the curve, is there a way to list names of all of the default

This is not mission critical, but it's bothering me. I'm getting inconsistent results when I use the $ accessor in the gam formula *In window #1:* > library(mgcv) > dat=data.frame(x=1:100,y=sin(1:100/50)+rnorm(100,0,.05)) > str(dat) > gam(dat$y~s(dat$x)) Error in eval(expr, envir, enclos) : object 'x' not found > *In window #2:* > gm = gam(dat$cf~s(dat$s)) >

The survexp function can fail when called from another function. The "why" of this has me baffled, however. Here is a simple test case, using a very stripped down version of survexp: survexp.test <- function(formula, data, weights, subset, na.action, rmap, times, cohort=TRUE, conditional=FALSE, ratetable=survexp.us, scale=1, npoints, se.fit,

> Does factanal() force the user to use the formula interface if they > wish to specify an na.action? Short answer: yes. Long answer: The handling of na.action is a built in part of the formula processing functions, so it's automatic when dealing with a formula. There are also downstream effects on predict() and resid() that are worked out for the formula case, but aren't clear