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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