View source: R/critical_value.R
compute_CV | R Documentation |
This function computes the critical value for two-sample kernel tests with centered Gaussian kernel using one of three methods: bootstrap, permutation, or subsampling.
compute_CV(
B,
Quantile,
data_pool,
size_x,
size_y,
h,
method,
b = 1,
compute_variance
)
B |
the number of bootstrap/permutation/subsampling samples to generate. |
Quantile |
the quantile of the bootstrap/permutation/subsampling distribution to use as the critical value. |
data_pool |
a matrix containing the data to be used in the test. |
size_x |
the number of rows in the |
size_y |
the number of rows in the |
h |
the tuning parameter for the kernel test. |
method |
the method to use for computing the critical value (one of "bootstrap", "permutation", or "subsampling"). |
b |
the subsampling block size (only used if |
compute_variance |
indicates if the nonparametric variance is computed. Default is TRUE. |
the critical value for the specified method and significance level.
Markatou Marianthi & Saraceno Giovanni (2024). “A Unified Framework for Multivariate Two- and k-Sample Kernel-based Quadratic Distance Goodness-of-Fit Tests.” https://doi.org/10.48550/arXiv.2407.16374
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