[R] opposite estimates from zeroinfl() and hurdle()

Tord Snäll tord.snall at ekol.slu.se
Fri Oct 23 12:33:10 CEST 2009


Dear all,
A question related to the following has been asked on R-help before, but 
I could not find any answer to it. Input will be much appreciated.

I got an unexpected sign of the "slope" parameter associated with a 
covariate (diam) using zeroinfl(). It led me to compare the estimates 
given by zeroinfl() and hurdle():

The (significant) negative estimate here is surprising, given the 
biology of the species:

 > summary(zeroinfl(bnl ~ 1| diam, dist = "poisson", data = valdaekar, 
EM = TRUE))
Count model coefficients (poisson with log link):
           Estimate Std. Error z value Pr(>|z|)   (Intercept)  
3.74604    0.02635   142.2   <2e-16 ***

Zero-inflation model coefficients (binomial with logit link):
           Estimate Std. Error z value Pr(>|z|)  (Intercept)  
21.7510     7.6525   2.842  0.00448 **
diam         -1.1437     0.3941  -2.902  0.00371 **

Number of iterations in BFGS optimization: 1
Log-likelihood: -582.8 on 3 Df


The hurdle model gives the same estimates, but with opposite (and 
expected) signs of the parameters:

summary(hurdle(bnl ~ 1| diam, dist = "poisson", data = valdaekar))
Count model coefficients (truncated poisson with log link):
           Estimate Std. Error z value Pr(>|z|)   (Intercept)  
3.74604    0.02635   142.2   <2e-16 ***
Zero hurdle model coefficients (binomial with logit link):
           Estimate Std. Error z value Pr(>|z|)  (Intercept) 
-21.7510     7.6525  -2.842  0.00448 **
diam          1.1437     0.3941   2.902  0.00371 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Number of iterations in BFGS optimization: 8
Log-likelihood: -582.8 on 3 Df

Why is this so?

thanks,
Tord
Windows NT, R 2.8.1, pcsl 1.03




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