plot.logbin.smooth: Default logbin.smooth Plotting

Description

The main use is to take a fitted logbin.smooth object produced by logbin.smooth and plot the component smooth functions that make it up, for specified values of the other covariates.

Alternatively, plots the model diagnostics usually provided by plot.lm.

Usage

# S3 method for logbin.smooth
plot(x, type = c("response", "link", "diagnostics"), at = data.frame(), 
     knotlines = TRUE, nobs = 1000, ...)

Arguments

a fitted logbin.smooth object as produced by logbin.smooth.

type

for "response" and "link", the type of prediction required. Note that, unlike predict.logbin.smooth, "terms" is not a valid option.

for "diagnostics", plot.lm is called.

a data frame containing the values at which the prediction should be evaluated. The columns must contain the covariates in the model, and several rows may be provided (in which case, multiple lines are drawn on the same plot). Cannot be missing or NULL.

knotlines

logical; if vertical lines should be drawn on the plot to indicate the locations of the knots for B-spline terms.

nobs

the number of points which should be used to create the curve. These are placed evenly along the range of the observed covariate values from the original model.

…

other graphics parameters to pass on to plotting commands, in particular any arguments to plot.lm (e.g. which).

Value

The function simply generates plots.

Details

For each smooth covariate in the model of x, predict.logbin.smooth is used to obtain predicted values for the range of that covariate, with the other covariates remaining fixed at their values given in at. Several rows may be provided in at, in which case, one curve is drawn for each, and they are coloured using rainbow(nrow(at)). If the model contains a single smooth covariate and no other covariates, at may be provided as an empty data frame, data.frame().

Examples

Run this code

# NOT RUN {
## For an example, see example(logbin.smooth)
# }