Dear Marc + List,
The real result trap often occurs with binomial logistic regression when there are extreme values (0 or N[i]) in the response. It appears that avoiding direct use of the logit link and using the inverse instead is more stable in these cases:
y[i] ~ dbin(theta[i], N[i])
eta[i] <- alpha + beta*x[i] ... etc
theta[i] <- 1/(1+exp(-eta[i]))
... which generally seems to work and I think is not quite as inelegant as arbitrarily truncating the linear predictor.
Bob Burn
Robert W. Burn
Independent Consultant
119 Northcourt Avenue
Reading RG2 7HG, UK
tel: +44 (0)118 326 5074
-----------------------------------
Visiting Research Fellow
Applied Statistics
School of Mathematical and Physical Sciences
University of Reading
-----Original Message-----
From: (The BUGS software mailing list) [mailto:[log in to unmask]] On Behalf Of Kery Marc
Sent: 07 October 2010 09:34
To: [log in to unmask]
Subject: [BUGS] AW: [BUGS] Help with winBUGS
Dear Colin,
I have quite often encountered the undefined real result trap when using logistic regressions, i.e., the logit link. A colleage told me the following trick, which seems to avoid numerical over- or underflow and has usually worked for me.
- Stabilized logit: To avoid numerical over- or underflow, you may "stabilise" the logit function by excluding extreme values (B. Wintle, pers. comm.). Here's a sketch of how to do that. The Gibbs sampling will typically get slower, but at least WinBUGS will be less likely to crash:
logit(psi.lim[i]) <- lpsi.lim[i]
lpsi.lim[i] <- min(999, max(-999, lpsi[i]))
lpsi[i] <- alpha.occ + beta.occ * something[i]
BTW, I'd be happy to have comments on the "kosher-ness" of this.
Regards -- Marc
______________________________________________________________
Marc Kéry
Tel. ++41 41 462 97 93
[log in to unmask]
www.vogelwarte.ch
Swiss Ornithological Institute | Seerose 1 | CH-6204 Sempach | Switzerland ______________________________________________________________
***** "Statistics is learning, and learning is the process of science." Don Berry *****
***** Check out my brand new book on Bayesian statistical modeling at www.mbr-pwrc.usgs.gov/pubanalysis/kerybook
-----Ursprüngliche Nachricht-----
Von: (The BUGS software mailing list) [mailto:[log in to unmask]]Im Auftrag von Colin O' Hare
Gesendet: Donnerstag, 7. Oktober 2010 01:50
An: [log in to unmask]
Betreff: [BUGS] Help with winBUGS
Dear List
I have got the spatial and non-spatial models working when I allow for only the age covariate now so thanks for all your help with that. However, when I allow for all covariates (income, age profiles, education etc) and using the same adj matrix to identify neighbours etc. I am coming up with an undefined real result trap when I update the model. Thanks for all your help so far, any further help greatly appreciated.
The model, data and initial values file are attached.
Kind regards
Colin O'Hare
Programme Director BSc Actuarial Science and Risk Management Queen's University Management School
25 University Square
Belfast
Northern Ireland
UK
BT7 1NN
Tel: 028 9097 2522
Fax: 028 9097 5156
Email: [log in to unmask]
URL: http://www.qub.ac.uk/mgt/
Model file (Spatial case):
model {
for (i in 1:N) {
Number[i] ~ dbin(Death[i], Population[i])
logit(Death[i]) <- alpha0 + alpha1 * Employment[i] + alpha2 * Age[i] + alpha3 * Income[i] + alpha4 * Health[i] + alpha5 * Education[i] + alpha6 * Environment[i] + alpha7 * Crime[i] + alpha8 * Proximity[i] + alpha35 * Income[i] * Education[i] + alpha31 * Income[i] * Employment[i] + alpha14 * Employment[i] * Health[i] + alpha18 * Employment[i] * Proximity[i] + alpha17 * Employment[i] * Crime[i] + W[i]
}
# CAR Prior Distribution for Random Effects:
W[1:N] ~ car.normal(adj[], weights[], neighbours[], lambda)
# Priors
alpha0 ~ dunif(-100, 100)
alpha1 ~ dunif(-100, 100)
alpha2 ~ dunif(-100, 100)
alpha3 ~ dunif(-100, 100)
alpha4 ~ dunif(-100, 100)
alpha5 ~ dunif(-100, 100)
alpha6 ~ dunif(-100, 100)
alpha7 ~ dunif(-100, 100)
alpha8 ~ dunif(-100, 100)
alpha35 ~ dunif(-100, 100)
alpha31 ~ dunif(-100, 100)
alpha14 ~ dunif(-100, 100)
alpha18 ~ dunif(-100, 100)
alpha17 ~ dunif(-100, 100)
lambda ~ dgamma(0.001, 0.001)
}
Initial values File (Spatial Case):
list(
alpha0 = 0, alpha1 = 0, alpha2 = 0, alpha3 = 0,
alpha4 = 0, alpha5 = 0, alpha6 = 0, alpha7 = 0,
alpha8 = 0, alpha35 = 0, alpha31 = 0, alpha14 = 0, alpha18 = 0, alpha17 = 0, lambda = 1, W = c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
)
Model File: (Non-Spatial case)
model {
for (i in 1:N) {
Number[i] ~ dbin(Death[i], Population[i])
W[i] ~ dnorm(0,tau)
V[i] ~ dnorm(0,tau2)
logit(Death[i]) <- alpha0 + alpha1 * Employment[i] + alpha2 * Age[i] + alpha3 * Income[i] + alpha4 * Health[i] + alpha5 * Education[i] + alpha6 * Environment[i] + alpha7 * Crime[i] + alpha8 * Proximity[i] + alpha35 * Income[i] * Education[i] + alpha31 * Income[i] * Employment[i] + alpha14 * Employment[i] * Health[i] + alpha18 * Employment[i] * Proximity[i] + alpha17 * Employment[i] * Crime[i] + W[i]+V[i]
}
# Priors
alpha0 ~ dunif(-1000, 1000)
alpha1 ~ dunif(-1000, 1000)
alpha2 ~ dunif(-1000, 1000)
alpha3 ~ dunif(-1000, 1000)
alpha4 ~ dunif(-1000, 1000)
alpha5 ~ dunif(-1000, 1000)
alpha6 ~ dunif(-1000, 1000)
alpha7 ~ dunif(-1000, 1000)
alpha8 ~ dunif(-1000, 1000)
alpha35 ~ dunif(-1000, 1000)
alpha31 ~ dunif(-1000, 1000)
alpha14 ~ dunif(-1000, 1000)
alpha18 ~ dunif(-1000, 1000)
alpha17 ~ dunif(-1000, 1000)
tau ~ dgamma(0.001, 0.001)
tau2~dgamma(0.001,0.001)
}
Initial File (non-spatial case)
list(
alpha0 = 0, alpha1 = 0, alpha2 = 0, alpha3 = 0,
alpha4 = 0, alpha5 = 0, alpha6 = 0, alpha7 = 0,
alpha8 = 0, alpha35 = 0, alpha31 = 0, alpha14 = 0,
alpha18 = 0, alpha17 = 0,
tau = 1,
tau2=1,
W = c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
V = c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
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0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)
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-------------------------------------------------------------------
This list is for discussion of modelling issues and the BUGS software.
For help with crashes and error messages, first mail [log in to unmask]
To mail the BUGS list, mail to [log in to unmask]
Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html
Please do not mail attachments to the list.
To leave the BUGS list, send LEAVE BUGS to [log in to unmask]
If this fails, mail [log in to unmask], NOT the whole list
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