similar to: binomial()$linkinv no longer accepts integer values

On Wed, 8 Jan 2025 10:57:47 -0500 Ben Bolker <bbolker at gmail.com> wrote: > I haven't done the archaeology to figure out when this broke/exactly > what change in the R code base broke it: it happened within the last > month or so binomial() itself exhibits this property even in R-4.2.2 from more than two years ago: R -q -s -e 'getRversion(); binomial()$linkinv(1L)'

Thanks, that makes sense. I guess if it never worked for integers (or hasn't worked in a long time, at least) then it doesn't need to be fixed/changed ... cheers Ben On 2025-01-08 11:20 a.m., Ivan Krylov wrote: > On Wed, 8 Jan 2025 10:57:47 -0500 > Ben Bolker <bbolker at gmail.com> wrote: > >> I haven't done the archaeology to figure out when this

On 1/8/25 17:26, Ben Bolker wrote: > Thanks, that makes sense. > > ? I guess if it never worked for integers (or hasn't worked in a long > time, at least) then it doesn't need to be fixed/changed ... Still you found out that the type check and use of REAL() in the function is in wrong order. Instead of "REAL() can only be applied to a 'numeric', not a

> On 9 Jan 2025, at 05:56, Tomas Kalibera <tomas.kalibera at gmail.com> wrote: > > > On 1/8/25 17:26, Ben Bolker wrote: >> Thanks, that makes sense. >> >> I guess if it never worked for integers (or hasn't worked in a long time, at least) then it doesn't need to be fixed/changed ... > > Still you found out that the type check and use of

thank you for your quick answer, I'm far of the digits capacity and my values are not the result of a computation. I'm developping a R package to acces a specific data source. And I need precision a few better. How can I do ? When I try this In R console, this is correct and what I need : > my_value <- 29.958334 > my_value == 29.958334 [1] TRUE But I need to do the first

ok, sorry, my mistake was the C printf. Thank you for your good answer Regards ----- Message d'origine ---- De : JS Ubei <jsubei at yahoo.fr> ? : jim holtman <jholtman at gmail.com> Cc : r-help at r-project.org Envoy? le : Jeudi, 17 Juillet 2008, 15h25mn 07s Objet : [R] Re : float and double precision with C code thank you for your quick answer, I'm far of the digits

Hi folks, I have a question about how to efficiently produce random numbers from Beta and Binomial distributions. For Beta distribution, suppose we have two shape vectors shape1 and shape2. I hope to generate a 10000 x 2 matrix X whose i th rwo is a sample from reta(2,shape1[i]mshape2[i]). Of course this can be done via loops: for(i in 1:10000) { X[i,]=rbeta(2,shape1[i],shape2[i]) } However,

Here's a patch that should make predict.glm(..., type="response") retain the names. The change passes make check on our Opteron running SLES9. One simple test is: names(predict(glm(y ~ x, family=binomial, data=data.frame(y=c(1, 0, 1, 0), x=c(1, 1, 0, 0))), newdata=data.frame(x=c(0, 0.5, 1)), type="response")) which gives [1]

Dear R users, I'm struggling with applying a user-defined link function in lmer. For analyzing data of a 2AFC psychophysical experiment, I would like to model my binary data with a logistic function with a lower limit at 0.5 instead of 0. In a previous question this has been described as a halflogit function. To do so I wrote my own link function and would like to submit it to lmer, however

Hello List, I am modeling a binomial response (nest survival) and I want to incorporate a random effect, in this case site. I had previously been using glm with a custom link function, but my understanding is that lmer does not currently allow a custom link. Therefore, I was investigating if other procedures for mixed models will allow a custom link function. here is the custom link function:

Dear all I am using NAMESPACE in my package but I would like the user to be able to overwrite four functions: own.linkfun, own.linkinv, own.mu.eta and own.valideta. These are used to defined "own" link functions. Is there any way of doing that without getting the when I am checking the package? This is what I am getting: make.link.gamlss : linkfun: no visible binding for global

G'day all, I had a look at the GLM code of R (1.4.1) and I believe that there are problems with the function "glm.fit" that may bite in rare circumstances. Note, I have no data set with which I ran into trouble. This report is solely based on having a look at the code. Below I append a listing of the glm.fit function as produced by my system. I have added line numbers so that I

Hi, I wish to write a new link function for a GLM. R's glm routine does not supply the "loglog" link. I modified the make.link function adding the code: }, loglog = { linkfun <- function(mu) -log(-log(mu)) linkinv <- function(eta) exp(-exp(-eta)) mu.eta <- function(eta) exp(-exp(-eta)-eta) valideta <- function(eta) all(eta != 0)

Hello All, I am looking for an R library/function that allows the specification of a custom link function in a linear mixed model. I've been using glm() in library MASS to fit fixed-effect models with a custom link but my study design demands mixed models. Any suggestions on the best R library/function to achieve this would be greatly appreciated. I have tried, to no avail, to

Greetings: I'm running R2.6.2 on a WinXP DELL box with 2 gig RAM. I have created a new glm link function to be used with family = binomial. The function works (although any suggested improvements would be welcome), logit.FC <- function(POD.floor = 0, POD.ceiling =1) { if (POD.floor < 0 | POD.floor > 1) stop ("POD.floor must be between zero and one.") if

Greetings, everyone. I've been trying to analyze bird nest survival data using generalized linear mixed models (because we documented several consecutive nesting attempts by the same individuals; i.e. repeated measures data) and have been unable to persuade the various GLMM models to work with my user-defined link function. Actually, glmmPQL seems to work, but as I want to evaluate a suite of

Dear R-Users, I wish to create a new family object based on the Binomial family. The only difference will be with the link function. Thus instead if using the 'logit(u)' link function, i plan to use '-log(i-u)'. So far, i have tried to write the function following that of the Binomial and Negative Binomial families. The major problem i have here is with the definition of the

Hi all, I've now got a problem with some modified lmer code (function lmer1 pasted at end) - I've made only three changes to the lmer code (marked), and I'm not really looking for comments on this function, but would like to know why execution of the following commands that use it almost invariably (but not quite predictably) leads to the R session terminating. Here's the command

Dear All, I have been trying to simulate data from a fitted glm using the simulate() function (version details at the bottom). This works for lm() fits and even for lmer() fits (in lme4). However, for glm() fits its output does not make sense to me -- am I missing something or is this a bug? Consider the following count data, modelled as gaussian, poisson and binomial responses: counts

I imitated predict.glm, my thing worked, now I need to revise. It would help me very much if someone would explain predict.glm line 28, which says object$na.action <- NULL # kill this for predict.lm calls I want to know 1) why does it set the object$na.action to NULL 2) what does the comment after mean? Maybe I need a pass by value lesson too, because I can't see how changing that