Description Usage Arguments Value See Also Examples

This function provides generalzied kernel-based two-sample tests.

1 |

`X` |
The first samples. |

`Y` |
The second samples. |

`sigma` |
The bandwidth of Gaussian kernels. The median heuristic should be used. |

`r1` |
The constant in the test statistics |

`r2` |
The constant in the test statistics |

`perm` |
The number of permutations performed to calculate the p-value of the test. The default value is 0, which means the permutation is not performed and only approximated p-value based on the asymptotic theory is provided. Doing permutation could be time consuming, so be cautious if you want to set this value to be larger than 10,000. |

Returns a list `teststat`

with each test statistic value and a list `pval`

with p-values of the tests. See below for more details.

`GPK` |
The value of the test statistic GPK |

`ZW1` |
The value of the test statistic |

`ZW2` |
The value of the test statistic |

`ZD` |
The value of the test statistic |

`fGPK_appr` |
The approximated p-value of fGPK based on asymptotic theory. |

`fGPKM_appr` |
The approximated p-value of |

`fGPK_Simes_appr` |
The approximated p-value of fGPK based on asymptotic theory with a Simes procedure. |

`fGPKM_Simes_appr` |
The approximated p-value of |

`GPK_perm` |
The permutation p-value of GPK when argument ‘perm’ is positive. |

`fGPK_perm` |
The permutation p-value of fGPK when argument ‘perm’ is positive. |

`fGPKM_perm` |
The permutation p-value of |

`fGPK_Simes_perm` |
The permutation p-value of fGPK with a Simes procedure when argument ‘perm’ is positive. |

`fGPKM_Simes_perm` |
The permutation p-value of |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
## Mean difference in Gaussian distribution.
d = 100
mu = 0.2
sam = 100
n = 200
set.seed(500)
X = matrix(rnorm(d*sam), sam)
Y = matrix(rnorm(d*sam,mu), sam)
sigma = med_sigma(X, Y) # median heuristic
a = kertests(X, Y, sigma, r1=1.2, r2=0.8, perm=1000)
# output results based on the permutation and the asymptotic results
# the test statistic values can be found in a$teststat
# p-values can be found in a$pval
``` |

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