test {fbglm} | R Documentation |
Vuong closeness test for zero-inflated models
Description
Compare zero-inflated regression models via Vuong closeness test.
Usage
test(y, x, model1, model2)
Arguments
y |
A response vector. |
x |
A data frame with covariates. |
model1 |
A character; one of "ZINB", "ZIP", "ZINB2", and "fbglm". |
model2 |
A character; one of "ZINB", "ZIP", "ZINB2", and "fbglm". |
Details
Perform one-tailed Vuong closeness test with the null hypothesis that the two models are equally close to the true data generating process, against the alternative that one model 1 is closer than model 2.
Choose model1
and model2
from zero-inflated negative binomial regression ("ZINB"), extended zero-inflated negative
binomial regression ("ZINB2"), zero-inflated Poisson regression ("ZIP"), and fractional binomial regression ("fbglm").
For "ZINB2" and "fbglm", see "fbglm::ZINB2" and "fbglm::fbglm" for details.
In "ZIP" and "ZINB", all the covariates are used as regressors in both the count and zero-inflation component.
Value
One-sided p-value will be returned.
References
Vuong, Quang H. (1989). Likelihood Ratio Tests for Model Selection and non-nested Hypotheses. Econometrica. 57 (2): 307–333.
Examples
library(agridat)
library(bbmle)
sample<-sample(270, 30)
my_y<-ridout.appleshoots$roots[sample]
my_x<-data.frame(pho=ridout.appleshoots$pho[sample])
test( y=my_y, x=my_x , "fbglm", "ZINB2" )