dr.permutation.test: Permutation tests of dimension for dr
In dr: Methods for Dimension Reduction for Regression

Description Usage Arguments Details Value Author(s) References See Also Examples

Approximates marginal dimension test significance levels for sir, save, and phd by sampling from the permutation distribution.

1	dr.permutation.test(object, npermute=50,numdir=object$numdir)

`object`	a dimension reduction regression object created by dr
`npermute`	number of permutations to compute, default is 50
`numdir`	maximum permitted value of the dimension, with the default from the object

The method approximates significance levels of the marginal dimension tests based on a permutation test. The algorithm: (1) permutes the rows of the predictor but not the response; (2) computes marginal dimension tests for the permuted data; (3) obtains significane levels by comparing the observed statsitics to the permutation distribution.

The method is not implemented for ire.

Returns an object of type ‘dr.permutation.test’ that can be printed or summarized to give the summary of the test.

Sanford Weisberg, sandy@stat.umn.edu

See www.stat.umn.edu/arc/addons.html, and then select the article on dimension reduction regression or inverse regression.

dr

data(ais)
attach(ais)  # the Australian athletes data
#fit dimension reduction regression using sir
m1 <- dr(LBM~Wt+Ht+RCC+WCC, method="sir", nslices = 8)
summary(m1)
dr.permutation.test(m1,npermute=100)
plot(m1)