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

In catherinewang1/assist: A Suite of R Functions Implementing Spline Smoothing Techniques

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 class '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.

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.

Author(s)

Chunlei Ke chunlei\[e-mail] and Yuedong Wang [e-mail]

See Also

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

Examples

## Not run: 
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")

## End(Not run)

catherinewang1/assist documentation built on June 16, 2019, 1:36 p.m.