Cook's Distance for Negative Binomial and Beta-Binomial Models
Produces an approximation, better known as the one-step approximation, of the Cook's distance, which is aimed to measure the effect on the estimates of the parameters in the linear predictor of deleting each observation in turn. This function also can produce an index plot of the Cook's distance for all parameters in the linear predictor or for some subset of them.
## S3 method for class 'overglm' cooks.distance(model, plot.it = TRUE, coefs, identify, ...)
model |
an object of class overglm obtained from the fit of a negative binomial or beta-binomial model. |
plot.it |
an (optional) logical indicating if the plot is required or just the data matrix in which that plot is based. By default, |
coefs |
an (optional) character string which (partially) match with the names of some model parameters. |
identify |
an (optional) integer indicating the number of individuals to identify on the plot of the Cook's distance. This is only appropriate if |
... |
further arguments passed to or from other methods. If |
The Cook's distance consists of the distance between two estimates of the parameters in the linear predictor using a metric based on the (estimate of the) variance-covariance matrix. The first one set of estimates is computed from a dataset including all individuals, and the second one is computed from a dataset in which the i-th individual is excluded. To avoid computational burden, the second set of estimates is replaced by its one-step approximation. See the dfbeta.overglm documentation.
A matrix as many rows as individuals in the sample and one column with the values of the Cook's distance.
## Cook's distance for all parameters in the linear predictor
fit <- overglm(cbind(cells,200-cells) ~ tnf + ifn + tnf*ifn, family="bb(logit)", data=cellular)
cooks.distance(fit, col="red", lty=1, lwd=1, col.lab="blue", main="Cook's distance",
col.axis="blue", col.main="black", family="mono", cex=0.8)
## Cook's distance for the parameter associated to the interaction
cooks.distance(fit, coef="tnf:ifn", col="red", lty=1, lwd=1, col.lab="blue",
main="Cook's distance", col.axis="blue", col.main="black",
family="mono", cex=0.8)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.