Hi,
I am new to R and has been depending mostly on the online tutotials to learn
R. I have to deal with zero inflated negative binomial distribution. I am
however unable to understand the following example from this link
http://www.ats.ucla.edu/stat/r/dae/zinbreg.htm
The result gives two blocks.
*library(pscl)
zinb<-zeroinfl(count ~ child + camper | persons, dist = "negbin", EM = TRUE)
summary(zinb)
*Call:
zeroinfl(formula = count ~ child + camper | persons, dist = "negbin",
EM = TRUE)
Count model coefficients (negbin with log link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.3711 0.2561 5.353 8.63e-08 ***
child -1.5152 0.1956 -7.747 9.42e-15 ***
camper 0.8790 0.2693 3.264 0.00110 **
Log(theta) -0.9854 0.1759 -5.601 2.14e-08 ***
Zero-inflation model coefficients (binomial with logit link):
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1.6028 0.8363 1.917 0.0553 .
persons -1.6662 0.6789 -2.454 0.0141 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Theta = 0.3733
Number of iterations in BFGS optimization: 2
Log-likelihood: -432.9 on 6 Df
What does this mean? What is the significance of "| persons" in the example?
Is the complete summary the full model? When I tried to use it, I got an
independent variable, which had a z- value of 0.005 in the second block. How
should i infer?
Thanks and Regards,
Vishnu B
Research Scholar,
Transportation Engineering Division,
IIT Madras,
Chennai 600036
Mob: +919445069977
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