msir (version 1.3.1)

msir.permutation.test: Permutation test for dimensionality

Description

Approximates marginal dimension test significance levels by sampling from the permutation distribution.

Usage

msir.permutation.test(object, npermute = 99, numdir = object$numdir, verbose = TRUE)

Arguments

object

a 'msir' object.

npermute

number of permutations to compute.

numdir

maximum value of the dimension to test.

verbose

if TRUE a textual progress bar is shown during computation.

Value

The function returns a list with components:

summary

a table containing the hypotheses, the test statistics, the permutation p-values.

npermute

the number of permutations used.

Furthermore, it also assigns the above information to the corresponding 'msir' object.

Details

The function approximates significance levels of the marginal dimension tests based on a permutation test.

References

Scrucca, L. (2011) Model-based SIR for dimension reduction. Computational Statistics & Data Analysis, 55(11), 3010-3026.

See Also

dr

Examples

# NOT RUN {
# 1-dimensional simple regression
n = 200; p = 5
b = as.matrix(c(1,-1,rep(0,p-2)))
x = matrix(rnorm(n*p), nrow = n, ncol = p)
y = exp(0.5 * x%*%b) + 0.1*rnorm(n)
MSIR = msir(x, y)
msir.permutation.test(MSIR)
summary(MSIR)
# }