assist (version 3.1.9)

plot.bCI: Bayesian Confidence Interval Plot of a Smoothing Spline Fit

Description

Create trellis plots of a nonparametric function fit together with its (approximate) 95% Bayesian confidence intervals from a ssr/slm/snr/snm object.

Usage

# S3 method for bCI
plot(x, x.val=NULL, type.name=NULL, ...)

Arguments

x

an object of class "bCI" containing point evaluation of the unknown function and/or corresponding posterior standard devaitions.

x.val

an optional vector representing values of argument based on which the function is to evaluate.

type.name

an optional character vector specifying the names of fits.

...

options suitable for xyplot.

Author

Chunlei Ke and Yuedong Wang

Details

This function is to visualize a spline fit by use of trellis graphic facility with Bayesian confidence intervals superposed. Multi-panel plots, based on xyplot, are suitable for SS ANOVA decomposition of a spline estimate.

See Also

predict.ssr, intervals.slm, intervals.snr, intervals.snm

Examples

if (FALSE) {
x<- seq(0, 1, len=100)
y<- 2*sin(2*pi*x)+rnorm(x)*0.5

fit<- ssr(y~x, cubic(x))
p.fit<- predict(fit)
plot(p.fit)
plot(p.fit,type.name="fit")
}