glm.cis {GLMpack} | R Documentation |
Compute confidence intervals for predictions.
Description
Apply an exponential transformation to the confidence intervals and predictions from binomial and Poisson models.
Usage
glm.cis(preds, ses, alpha, df)
Arguments
preds |
The predictions based on the additive linear component of the model. |
ses |
The standard error(s) of the prediction. |
alpha |
The desired confidence level. |
df |
The desired degrees of freedom. |
Value
The output is a matrix.
Examples
data(campaign)
attach(campaign)
cmpgn.out <- glm(TOTCONTR ~ CANDGENDER + PARTY + INCUMCHALL + HISPPCT,
family=Gamma(link = 'log'), data=campaign)
newdat_gender <- data.frame(CANDGENDER = c('F','M'), PARTY= rep('Democrat',2),
INCUMCHALL=rep("C", 2), HISPPCT=rep(mean(campaign$HISPPCT),2))
preds_gender <- predict(cmpgn.out, newdata = newdat_gender, se.fit = TRUE)
glm.cis(preds_gender$fit, preds_gender$se.fit, 0.95,cmpgn.out$df.residual)
[Package GLMpack version 0.1.0 Index]