Displaying 1 result from an estimated 1 matches for "obsvpred".
2007 Aug 09
2
Systematically biased count data regression model
...viance: 515.16 on 253 degrees of freedom
Residual deviance: 278.89 on 246 degrees of freedom
AIC: 1300.1
Number of Fisher Scoring iterations: 1
Theta: 11.35
Std. Err.: 2.71
2 x log-likelihood: -1282.075
#Plotting observed versus predicted values.
pdf(file="ObsVPred.pdf", width=4, height=4, family="Times", pointsize=11)
par(mar = c(5,5,1,1), pch=1)
plot(data$D, fit$fitted.values, main="",
ylab=expression(italic(D)[predicted]),
xlab=expression(italic(D)[observed]))
abline(a=0,b=1, lty=2)
lines(lowess(data$D, fit$fitted.values))
dev.off(...