similar to: using betareg: problems with anova and predict

Hello, I have a dataset with proportions that vary around a fixed mean, is it possible to use betareg to look at variance in the dispersion parameter while keeping the mean fixed? I am very new to R but have tried the following: svec<-c(qlogis(mean(data1$scaled)),0,0,0) f<-betareg(scaled~-1 | expt_label + grouped_hpi, data=data1, link.phi="log",

Hi I'm trying to fit a model in betareg and I'm getting errors, but have no idea what they mean or how to solve them. Does anyone have experience with this? > model <- betareg(ACT ~ ST*SoilT, data = actDL_F) Warning messages: 1: In sqrt(W) : NaNs produced 2: In sqrt(W) : NaNs produced 3: In sqrt(1 + phihat) : NaNs produced data summaries don't give any na's or problems I

Dear all, I get an error using betrag on this data set :http://dl.dropbox.com/u/1866110/dump.csv. I run it like this regression f2.1=betareg(Y~X1+X2,data=dump) summary(f2.1) I get : Call: betareg(formula = Y ~ X1 + X2, data = dump) Standardized weighted residuals 2: Error in quantile.default(x$residuals) : missing values and NaN's not allowed if 'na.rm' is FALSE In addition:

Folks, The betareg package appears to be polished and works well. But I would like to look at the exact formulas for the underlying model being estimated, the likelihood function, etc. E.g. if one has to compute \frac{\partial E(y)}{\partial x_i}, this requires careful calculations through these formulas. I read "Regression analysis of variates observed on (0,1): percentages, proportions and

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

Hi, In using the betareg package, I encounter the following error message: Error in lm.wfit(x, linkfun(y), weights, offset = offset) : NA/NaN/Inf in foreign function call (arg 4) Any help will be most appreciated. Thanks in advance. Alex

Dear useRs, version 2.2-2 of the "betareg" package has just been released on CRAN http://CRAN.R-project.org/package=betareg accompanied by an article in the Journal of Statistical Software http://www.jstatsoft.org/v34/i02/ The package provides beta regression for data in the unit interval (0, 1) such as rates and proportions. The manuscript replicates several practical

Dear useRs, version 2.2-2 of the "betareg" package has just been released on CRAN http://CRAN.R-project.org/package=betareg accompanied by an article in the Journal of Statistical Software http://www.jstatsoft.org/v34/i02/ The package provides beta regression for data in the unit interval (0, 1) such as rates and proportions. The manuscript replicates several practical

Dear all, we received a bug report for betareg, that in some cases the optim call in betareg.fit would hang the R session and the command cannot be interrupted by Ctrl-C? We narrowed down the problem to the dbeta function which is used for the log likelihood evaluation in betareg.fit. Particularly, the following command hangs the R session to a 100% CPU usage in all systems we tried it (OS X

Hi, what's mean "/" in command: betareg(inf~Grupo/Sexo, data=dados) it's a effect nested? -------------------------------------- Silvano Cesar da Costa Departamento de Estat?stica Universidade Estadual de Londrina Fone: 3371-4346

Stephen, thanks for your effort. The more appropriate list for this discussion is probably R-devel (as far as I understand it) so I've moved the discussion there. Related topics have already been discussed in the past. Specifically, I remember contributions by Paul Johnson ("rockchalk" package) and John Fox ("effects" and "car" package) as their packages

Hello, I am currently working with the betareg package, which allows the fitting of a variable dispersion beta regression model (Simas et al. 2010, Computational Statistics & Data Analysis). I was wondering whether there is any package in R that allows me to fit variable dispersion parameters in the standard logistic regression model, that is to make the dispersion parameter contingent upon

Greetings, I am interested in using a generalized linear mixed model with data that best fits a beta distribution (i.e., the data is bounded between 0 and 1 but is not binomial). I noticed that the beta distribution is not listed as an option in the "family objects" for glmmPQL or lmer. I found a thread on this listserve from 2006 ("[R] lmer and a response that is a

Hi, Does anyone know of a function in R that can handle a fractional variable as the dependent variable? The catch is that the function has to be inclusive of 0 and 1, which betareg() does not. It seems like GLM might be able to handle the fractional logit model, but I can't figure it out. How do you format GLM to do so? Best, Rachael [[alternative HTML version deleted]]

Good morning, Does anyone know of a package or function to do a beta regression? Thanks, Walt Paczkowski _________________________________ Walter R. Paczkowski, Ph.D. Data Analytics Corp. 44 Hamilton Lane Plainsboro, NJ 08536 (V) 609-936-8999 (F) 609-936-3733

Dear all, I am trying to get an estimate of uncertainty surrounding a single predicted value from a beta regression model (this is similar to a logistic glm - in that it involves a link function and linear predictor - but it uses the beta distribution rather than discrete binomial). For example: library(betareg) data("GasolineYield")

Good morning, I am using R to try to model the proportion of burned area in Portugal. The dependent variable is the proportion. The family used is binomial and the epsilon would be binary. I am not able to find the package to be used when the proportion (%) has to be used in glm. Could someone help me? I am using normal commands of glm.. for example: glm_5<- glm(formula=p~Precipitation,

Buenas tardes, Estoy interesado en ajustar modelos de regresion beta {betareg} a un conjunto de datos en el que se tienen una variable respuesta "y" y ~600K variables independientes. En el codigo en R que se encuentra en la parte inferior presento un ejemplo en el que se tienen 500 variables independientes y la misma respuesta "y" para todos. Tambien se encuentran algunos

Hi, I want to fit 3 beta distributions to my data which ranges between 0 and 1. What are the functions that I can easily call and specify that 3 beta distributions should be fitted? I have already looked at normalmixEM and fitdistr but they dont seem to be applicable (normalmixEM is only for fitting normal dist and fitdistr will only fit 1 distribution, not 3). Is that right? Also, my data has 26

Hello, dear experts. I don't have much experience in building regression models, so sorry if this is too simple and not very interesting question. Currently I'm working on the model that have to predict proportion of the debt returned by the debtor in some period of time. So the dependent variable can be any number between 0 and 1 with very high probability of 0 (if there are no payment)