cvModeApprox: Critical values for test statistic based on the approximating...

cvModeApproxR Documentation

Critical values for test statistic based on the approximating set of intervals

Description

This dataset contains critical values for some n and \alpha for the test statistic based on the approximating set of intervals, with or without additive correction term \Gamma.

Usage

data(cvModeApprox)

Format

A data frame providing 15 different combinations of n and \alpha and the following columns:

alpha The levels at which critical values were simulated.
n The number of observations for which critical values were simulated.
withadd Critical values based on T_n^+({\bf{U}}) and the approximating set of intervals \mathcal{I}_{app}.
noadd Critical values based on T_n({\bf{U}}) and the approximating set of intervals \mathcal{I}_{app}.

Details

For details see modeHunting. Critical values are based on M=100'000 simulations of i.i.d. random vectors

{\bf{U}} = (U_1,\dots,U_n)

where U_i is a uniformly on [0,1] distributed random variable, i=1,\dots,M.

Remember

n is the number of interior observations, i.e. if you are analyzing a sample of size m, then you need critical values corresponding to

n = m-2 If no additional information on a and b is available.
n = m-1 If either a or b is known to be a certain finite number.
n = m If both a and b are known to be certain finite numbers,

where [a,b] = \{x \ : \ f(x) > 0\} is the support of f.

Source

These critical values were generated using the function criticalValuesApprox. Critical values for other combinations for \alpha and n can be computed using this latter function.

References

Rufibach, K. and Walther, G. (2010). A general criterion for multiscale inference. J. Comput. Graph. Statist., 19, 175–190.

Examples

## extract critical values for alpha = 0.05, n = 200
data(cvModeApprox)
cv <- cvModeApprox[cvModeApprox$alpha == 0.05 & cvModeApprox$n == 200, 3:4]
cv

modehunt documentation built on June 8, 2025, 9:38 p.m.