sig.trace: A significance trace for a hypothesis test
In sm: Smoothing Methods for Nonparametric Regression and Density Estimation

Description Usage Arguments Details Value Side Effects References See Also Examples

This function creates a significance trace for a hypothesis test based on a nonparametric smoothing procedure. The p-value of the test is plotted against a range of smoothing parameters.

1	sig.trace(expn, hvec, ...)

`expn`	an S-Plus expression which should define the hypothesis test to be performed, with the value of the smoothing parameter `h` omitted from the function call.
`hvec`	a vector of smoothing parameters for which the test will be performed.
`...`	further arguments which will be passed to `sm.options`.

see Section 5.2 of the reference below.

Only tests involving a univariate smoothing parameter may be used.

a list containing vectors with the smoothing parameters and p-values.

If the largest p-value is greater than 0.05 then a horizontal line at 0.05 will be superimposed on any plot, for reference.

Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.

none.

x <- runif(50, 0, 1)
y <- 5*x^2 + rnorm(50)
sig.trace(sm.regression(x, y, model = "linear", display="none"), 
        hvec = seq(0.05, 0.3, length = 10))