View source: R/critical_value.R
cv_ksample | R Documentation |
This function computes the empirical critical value for the k-sample KBQD tests using the centered Gaussian kernel, with bootstrap, permutation, or subsampling.
cv_ksample(
x,
y,
h,
B = 150,
b = 0.9,
Quantile = 0.95,
method = "subsampling",
compute_variance = TRUE
)
x |
matrix containing the observations to be used in the k-sample test |
y |
vector indicating the sample for each observation |
h |
the tuning parameter for the test using the Gaussian kernel |
B |
the number of bootstrap/permutation/subsampling samples to generate |
b |
the subsampling block size (only used if |
Quantile |
the quantile of the bootstrap/permutation/subsampling distribution to use as the critical value |
method |
the method to use for computing the critical value (one of "bootstrap", "permutation") |
compute_variance |
indicates if the nonparametric variance is computed. Default is TRUE. |
a vector of two critical values corresponding to different formulation of the k-sample test statistics.
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