similar to: "NOTE" warning

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

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)

Hi, I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. Gamlss seems to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno

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 all I am trying to create a package in R 1.9.0 and I a getting an error message which I do not understand. (I am using R in Windows XP and 2000) For example the following works well in 1.8.1 C:\Program Files\R\rw1081\src\gnuwin32>make pkg-gamlss ---------- Making package gamlss ------------ adding build stamp to DESCRIPTION installing inst files installing indices not zipping

Dear list, I'm trying to mimic the analysis of Wedderburn (1974) as cited by McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on barley example, and the data is available in the `faraway' package. Wedderburn suggested using the variance function mu^2(1-mu)^2. This variance function isn't readily available in R's `quasi' family object, but it seems to me

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

Dear all I am trying to build a package in Windows. I use the following command (which it used to work with previous versions ) and I am getting the following error #-------------------------------------------------------------------------------------------------------------- C:\PROGRA~1\R\rw2000\bin>Rcmd build --binary --use-zip C:\PROGRA~1\R\rw2000\src\library\gamlss * checking for

Dear all and Mikis I have the opportunity to compare fits with the 'classical' glm and gamlss and no smoother of any kind just the same model formula (both with the binomial family). I get exactly the same coefficients but very different residuals, gamlss giving residuals which are extremely close to 'normal' and glm very far... How can this be ? Thanks in advance for

At useR 2006 I mentioned that it would be nice to have a way to specify binomial links that involved free parameters and described some experience with a Gosset link involving a free degrees of freedom parameter, and a Tukey-lambda link with two free parameters. My implementation of this involved some rather kludgey modifications of binomial, make.link and glm that (essentially) added a

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]

Hi all I am converting an S-Plus function into R. The S-Plus code uses some of the glm families, and family objects. The family objects in S-Plus and R have many different features, for example: In R: > names(Gamma()) [1] "family" "link" "linkfun" "linkinv" "variance" [6] "dev.resids" "aic"

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:

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

I would like to do an R glm() with family = binomial(link="loglog") Right now, the cloglog link exists, which is nice when the data have a heavy tail to the left. I have the opposite case and the loglog link is what I need. Can someone suggest how to add the loglog link onto glm()? It would be lovely to have it there by default, and it certainly makes sense to have the two opposite

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

Hello Mikis: Thanks a lot, it worked. Could you tell me what the problem was? Regards, Nik ----- Original Message ----- From: r-help-request at r-project.org To: "r-help" Sent: Sunday, March 11, 2018 6:00:02 AM Subject: R-help Digest, Vol 181, Issue 11 Send R-help mailing list submissions to r-help at r-project.org To subscribe or unsubscribe via the World Wide Web, visit

under "Details" (version 2015-11-29 r69717; not quite cutting-edge, but nothing has changed in src/library/stats/man/family.Rd in 5 months [sorry for using the Github mirror, but I prefer the interface ... <https://github.com/wch/r-source/blob/trunk/src/library/stats/man/family.Rd>]) it says: valid.mu: logical function. Returns ?TRUE? if a mean vector ?mu? is within the

I apologize for my earlier posting that, unbeknownst to me before, apparently was not in the correct format for this list. Hopefully this attempt will go through, and no-one will hold the newbie mistake against me. I could really use some help in writing a new glm link function in order to run an analysis of daily nest survival rates. I've struggled with this for weeks now, and can at least