Residuals for Negative Binomial and Beta-Binomial Regression Models
Calculates residuals for a fitted negative binomial or beta-binomial model.
## S3 method for class 'overglm'
residuals(
object,
...,
type = c("quantile", "standardized", "response"),
plot.it = TRUE,
identify
)object |
an object of the class overglm obtained from the fit of a negative binomial or beta-binomial model. |
... |
further arguments passed to or from other methods. |
type |
an (optional) character string giving the type of residuals which should be returned. The available options are: (1) the difference between the observed response and the fitted mean ("response"); (2) the standardized difference between the observed response and the fitted mean ("pearson"); (3) the randomized quantile residuals ("quantile"). By default, |
plot.it |
an (optional) logical switch indicating if a plot of the residuals is required. By default, |
identify |
an (optional) integer value indicating the number of individuals to identify on the plot of residuals. This is only appropriate when |
A vector with the observed residuals type type.
Dunn P.K. and Smyth G.K. (1996) Randomized Quantile Residuals. Journal of Computational and Graphical Statistics, 5, 236-244.
## Example 1
fit1 <- overglm(cbind(fetuses,litter-fetuses) ~ pht + tcpo, family="bb(logit)", data=ossification)
residuals(fit1,type="quantile",col="red", pch=20,col.lab="blue",
col.axis="blue",col.main="black",family="mono",cex=0.8)
## Example 2
fit2 <- overglm(infections ~ location + frequency, family="nb1(log)", data=swimmers)
residuals(fit2,type="quantile",col="red", pch=20,col.lab="blue",
col.axis="blue",col.main="black",family="mono",cex=0.8)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.