search for: pscl

Hello, I'm using GLMM on the pscl package and i'm not getting the AIC on the summary. The code i'm using is (example) : mmall3 <-glmmPQL(allclues ~ cycloc + male, data=dados, family=poisson, random=~1|animal/idfid) and the results: Linear mixed-effects model fit by maximum likelihood Data: dados AIC BIC logLik...

Dear R users, I want to apply zero inflated models with continuous and categorical variables and I used pscl package from R and the zeroinf() function. My question are the follow: a) The value of fitted.values is mu or (1-p)*mu? where p is the probability of zero came form a zero point mass b) If mu is zero, how do i know if it is a zero from the zero point mass or from the count process? Thank you s...

Hi, This may be such a general question that my searches are just failing. I installed the pscl lib, all appears fine, installed it several different ways to be sure, but I am getting: Error: could not find function "zeroinfl" I double checked my spelling of the function and that it had not been evolved out of the package. It is in the same location as the other libraries that are l...

Dear list, I'm currently trying to develop a model to assess clam yield potential in a lagoon. I'm using the zeroinfl function of the pscl package to fit a Zero-inflated negative binomial model, given the high occurrence of zero counts. I don't understand from the sentence in the pscl guide "Zero-inflated count models are a type of two-component mixture model, with a component for zero counts, and the other component for the...

Hi all, I have been trying to use zeroinfl() with the pscl package with R version 2.1.1. and with the newest versions of the contrib packages compatible with R 2.1.1. I have read the examples, the vignette and all the posts relating to zeroinfl() but I am still confused as to how to structure the model. Here is a small example; the error message is the s...

Dear R-Helpers, Can anyone please help me to interpret warning messages from zeroinfl (package pscl) while fitting a zero inflated negative binomial model? The console reports convergence and the parameters seam reasonable, but these <<Warning messages: 1: algorithm did not converge in: glm.fit(X, Y, family = poisson()) 2: fitted rates numerically 0 occurred in: glm.fit(X, Y, family = p...

Hi all, I'm trying to run some monte carlo simulation for my roll call data using the ideal() function, which resides in the pscl package. However, I'm receiving an error message that I don't understand. Error in ideal(a, maxiter = 1000, thin = 10, burnin = 50, store.item = TRUE, : NA/NaN/Inf in foreign function call (arg 13) my code is simple the following: > m_a <- ideal(a, maxiter = 1000, thin = 10, b...

...mselves. Thus, I'm looking at a recent JAMA article in which both numbers and dotplot of RR and 95% CI are presented and wondering about best way to do this in R. Essentially, the plot has 3 columns: variable names, RR and 95% CI, and dotplot of the same. Using the bioChemists data in the pscl package and errbar function in Hmisc package, the code below is in the right direction... but still pretty ugly. Wondering if folks would have alternative suggestions about how to go about this, or pointers on cleaning up the code below (eg, I know there are many functions for plotting errbars...

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The average estimates from code below are: count_(Intercept) count_trt zero_(...

...me). Therefore I need to account for the effort. If change the count (response variable) then it will have decimals and not be usable in this model. So I decided to put this term into the independent variable. I am analyzing Historic vs. Current surveys. Here is an example of my code: require(pscl) model <- zeroinfl(Sallys~Survey:Person.Hours, dist="poisson", EM=TRUE) summary(model) I have received some very significant results on most of them and on some that I thought wouldn't be significant turned out to be. So I am concerned with the model being appropriate. I created...

Sorry bit of a Newbie question, and I promise I have searched the forum already, but I'm getting a bit desperate! I have over-dispersed, zero inflated data, with variance greater than the mean, suggesting Zero-Inflated Negative Binomial - which I attempted in R with the pscl package suggested on http://www.ats.ucla.edu/stat/R/dae/zinbreg.htm However my data is non-integer with some pesky decimals (i.e. 33.12) and zinb / pscl doesn't like that - not surprising as zinb is for count data, normally whole integers etc. Does anyone know of a different zinb package that...

Hello all: I have a question regarding the fitted.values returned from the zeroinfl() function. The values seem to be nearly identical to those fitted.values returned by the ordinary glm(). Why is this, shouldn't they be more "zero-inflated"? I construct a zero-inflated series of counts, called Y, like so: b= as.vector(c(1.5, -2)) g= as.vector(c(-3, 1)) x <- runif(100) # x

This request is related to the following post from last year: https://stat.ethz.ch/pipermail/r-help/2011-June/279752.html After reading the thread, the idea is still not clear. I have fitted a model using HURDLE from the PSCL package. I am trying to get marginal effects / slopes by multiplying the coefficients by the mean of the marginal effects (I think this is right). To my understanding, this will require a mean for the binary probability model and a mean for the truncated Poisson count model. My guess is that I woul...

Dear list, I'm wondering if anyone can help me calculate the deviance of either a zeroinfl or hurdle model from package pscl? Even if someone could point me to the correct formula for calculating the deviance, I could do the rest on my own. I am trying to calculate a pseudo-R-squared measure based on the R^{2}_{DEV} of [1], so I need to be able to calculate the deviance of the full and null models. Does anyone have any...

...w predictors). I want to calculate r-squared for this model. I have been reading online about it and found there are multiple formulas for calculating R2 (psuedo) for glm (in R) with gaussian (r2 from linear model), logistic regression (1-deviance/null deviance), poisson distribution (using pR2 in pscl package, D-squared value from modEvA R package). But I could not find anything specific to gamma distributions. Can pscl and modEVA packages be used for gamma distributions as well? or there is any other formula for doing the same? Thanks Regards, Anchal -- Anchal Sharma, PhD Postdoctoral Fel...

Dear R helpers, running the following code of a glm model of the family poisson, gives predicted values < 0. Why? library(MASS) library(stats) library(mvtnorm) library(pscl) data(bioChemists) poisson_glm <- glm(art ~ fem + mar + kid5 + phd + ment, data = bioChemists, family = poisson) predicted.values = predict(poisson_glm) range(predicted.values) Thank you in advance for any hints. Best regards, P. Olsson [[alternative HTML version deleted]]

Hello, I'm using pscl to run a hurdle model. Everything works great until I get to the point of making predictions. All of my "count" predictions are lower than my actual data, and lower than the "response" predictions, similar to the issue described here ( https://stat.ethz.ch/pipermail/r-help/2012-...

Dear all, I'm using zeroinfl() from the pscl-package for zero inflated Poisson regression. I would like to calculate (aproximate) prediction intervals for the fitted values. The package itself does not provide them. Can this be calculated analyticaly? Or do I have to use bootstrap? What I tried until now is to use bootstrap to estimate these...

Hi, I have two questions. First, I'd like to compare a ZINB model to a negativ binomial model with the Vuong test, but I can't find how to performe it from the zicount package. Does a programm exist to do it ? Second, I'd like to know in which cases we have to use a double hurdle model instead of a zero inflated model. Many thanks, St??phanie Payet REES France R??seau

Hello ; I am doing a regression of count data (number of award and there are some covariates) I have estiamted the parameters of negative binomial distribuion (lambda is a function of covaraites, GLM model) by glm.nb function and training dataset. Now I want to predict the number of award (for example y=0, y=1, y=2,) or testing dataset. I dont know how to calculate this numbers? I would be very