msir (version 1.1)

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 and Data Analysis, 55(11), 3010-3026.

See Also

dr

Examples

# 1-dimensional simple regression
n = 200; p = 5
b = as.matrix(c(1,-1,rep(0,p-2)))
x = mvrnorm(n, rep(0,p), diag(p))
y = exp(0.5 * x%*%b) + 0.1*rnorm(n)
MSIR = msir(x, y)
msir.permutation.test(MSIR)
summary(MSIR)