# similar to: Zero inflation model - pscl package

Displaying 9 results from an estimated 9 matches similar to: "Zero inflation model - pscl package"

2006 Jul 20
0
Convergence warnings from zeroinfl (package pscl)
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 =
2008 Sep 19
0
problems with too many NA in the function ideal() from pscl package.
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
2012 Sep 10
1
Zero inflated Models- pscl package
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?
2008 Feb 18
1
fitted.values from zeroinfl (pscl package)
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
2012 Jan 17
2
pscl package and hurdle model marginal effects
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
2009 Dec 12
1