similar to: using loglog link in VGAM or creating loglog link for GLM

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 am new to R and would like to use it for fitting the zipf distribution to some numeric data that I have. Here's the snippet that I use: library(VGAM) X <- read.table(file("~\\mydata.txt", encoding="latin1")) w <- as.vector(t((X[2]))) w <- w/sum(w) y <- (1:length(w)) fit = vglm (y ~ 1, zipf, tra=TRUE, weight=w) zipf(N=NULL,

Help needed with lm function: Dear R's, Could anyone tell me how to replace the link function (probit logit, loglog etc.) in lm with an abitrary user-defined function? The task is to perform ML Estimation of betas for a dichotome target variable. Maybe there is already a package for this (I did not find one). Any hints or a code excerpt would be welcome! Thank you -Jeff jeff.pr2 (at)

Dear all, A looong time ago, Witold Eryk Wolski asked here why there wasn't a log="xy" parameter to the hist() function <URL:http://www.R-project.org/nocvs/mail/r-help/2001/0267.html>, and Prof. Ripley responded that a loglog histogram does not make much sense, and that one should use a better density estimate if one seeks to plot log density. I understand the point and I

Hi Folks, I wonderif someone who is familiar with the details of vglm in the VGAM package can assist me. I'm new to using it, and there doesn;t seem much in the documentation that's relevant to the question below. Say I have a vector x of 0/1 responses and another vector y of 0/1 responses, these in fact being a bivariate set of 0/1 responses equivalent to cbind(x,y). E.g.

I just discovered that when the VGAM package (not on CRAN) is loaded, glm() doesn't work. This is because VGAM defines a family function() which gets found by glm() in place of the family function from stats. Then VGAM:::family returns an object which doesn't have a $family component, (it has a component $vfamily). I thought namespaces should protect us from this happening? Kjetil --

Dear R Helpers This is the R code (which I have slightly changed) I got in VGAM package for estimating the parameters of FRECHET. _________________________________________________________________ y = rfrechet(n <- 100, shape=exp(exp(0))) # (A) fit3 = vglm(y ~ 1, frechet3(ilocation=0), trace=TRUE, maxit=155) # (B) coef(fit3, matrix=TRUE) # (C)

Hi to every body. I would like assistance on how to implement the log-log link function for binary response. Is there any package that implements it? Many thanks Endy [[alternative HTML version deleted]]

I'm having trouble using binomial(link="cloglog") with GLMM in lme4, Version: 0.5-2, Date: 2004/03/11. The example in the Help file works fine, even simplified as follows: fm0 <- GLMM(immun~1, data=guImmun, family=binomial, random=~1|comm) However, for another application, I need binomial(link="cloglog"), and this generates an error for me: >

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 R-Users, I have recently run into several problems using vgam() in the VGAM package. I am hoping someone might have some solutions... Briefly, I have been trying to fit GAM models for zero-altered negative binomial models. 1. When fitting smoothed parameters (e.g. s(X, df=2)) changing the degrees-of-freedom has no effect on the level of smoothing (e.g. number of knots for the

The symptom triggering this email is that an S4 summary method sometimes refuses to be invoked, even when a package is explicitly loaded, if the first load of the package is implicit. It may or may not be specific to 'summary' methods and/or the 'VGAM' package. I've sent to R-devel because (i) it looks like some kind of bug to me, but I'm not sure; (ii) it's not

I'm trying to use GLMM in library(lme4), R 1.9.0pat, updated just now. I get an error message I can't decipher: library(lme4) set.seed(1) n <- 10 N <- 1000 DF <- data.frame(yield=rbinom(n, N, .99)/N, nest=1:n) fit <- GLMM(yield~1, random=~1|nest, family=binomial, data=DF, weights=rep(N, n)) Error in eval(expr, envir, enclos) : ..1 used in an incorrect

Hi! R users I would like to ask you where could we find the VGAM Package. I don't find it in the list of packages. Thak you for your help Lassana KOITA Etudes de S?curit? et d'Exploitation a?roportuaires / Safety Study & Statistical analysis Service Technique de l'Aviation Civile (STAC) / Civil Aviation Technical Department Direction G?n?rale de l'Aviation Civile (DGAC) /

Hello, I have different results from these two softwares for a simple binomial GLM problem. >From Genmod in SAS: LogLikelihood=-4.75, coeff(intercept)=-3.59, coeff(x)=0.95 >From glm in R: LogLikelihood=-0.94, coeff(intercept)=-3.99, coeff(x)=1.36 Is there anyone tell me what I did wrong? Here are the code and results, 1) SAS Genmod: % r: # of failure % k: size of a risk set data

Dear, When i multiply the y of a regression by 10, I would expect that the coefficient would be multiply by 10 and the z value to stay constant. Here some reproducible code to support the case. *Ex 1* library(mvtnorm) library(VGAM) set.seed(1) x=rmvnorm(1000,sigma=matrix(c(1,0.75,0.75,1),2,2))

Dear R-help gurus (and T.Yee, the VGAM maintainer) - I've been banging my head against the keyboard for too long now, hopefully someone can pick up on the errors of my ways... I am trying to use optim to fit a zero-inflated negative binomial distribution. No matter what I try I can't get optim to recognize my initial parameters. I think the problem is that dnbinom allows either

Hello, I'm not a Stata user so I'm trying to reproduce Stata results that are given to me in R. I would like to use a GLM with a complementary log-log function. The stata code I have is: glm c IndA fia, family(binomial s) link(cloglog) offset(offset) The R code is: glmt <- glm(data=dataset, c ~ IndA + fia, offset = offset, family = binomial(link = cloglog)) Which yields

Hello R users, I have a puzzle with the VGAM package, on my first excursion into generalized additive models, in that this very nice package seems to want to do either more or less than what I want. Precisely, I have a 4-component outcome, y, and am fitting multinomial logistic regression with one predictor x. What I would like to find out is, is there a single nonlinear function f(x) which acts

This is to announce the new R-package ?ordinal? that implements cumulative link (mixed) models for ordinal (ordered categorical) data (http://www.cran.r-project.org/package=ordinal/). The main features are: - scale (multiplicative) as well as location (additive) effects - nominal effects for a subset of the predictors (denoted partial proportional odds when the link is the logistic) - structured