| count.fit {catregs} | R Documentation |
Fits four different count models and compares them.
Description
Given a Poisson model object, count.fit fits Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models to the data. It reports results of Vuong tests between the zero-inflated and non-zer-inflated models, summarizes the information criteria of the four models, summarizes the model output of the four models, creates a ggplot object of coefficient plots for each model, and creates a ggplot object of model residuals.
Usage
count.fit(m1,y.range,rounded=3,use.color="yes")
Arguments
m1 |
A Poisson regression model, as estimated via the glm function. |
y.range |
The observed response range for the count outcome. For example, if the observed range is 0 to 18, this would be 0:18 |
rounded |
The number of decimal places to round the output. The default is 3. |
use.color |
Whether to use color in the ggplot objects. Default is "yes" |
Value
ic |
A data.frame summarizing the information criteria for the four models. Bayesian and Akaike's informaiton criteria are included. |
models |
A summary of the model estimates, including coefficients and standard errors. |
pic |
A ggplot object illustrating model residuals for each type of model. |
models.pic |
A ggplot object of coefficient plots from each type of model. |
Author(s)
David Melamed
Examples
data("LF06art")
p1 <- glm(art ~ fem + mar + kid5 + phd + ment , family = "poisson", data = LF06art)
table(LF06art$art)
fit<-count.fit(p1,0:19)
names(fit)