cnnTest | R Documentation |

Permutation Test for cross-type nearest neighbor distances

cnnTest( dist, n1, n2, w = rep(1, n1 + n2), B = 999, alternative = "less", returnSample = TRUE, parallel = FALSE, ... )

`dist` |
a distance matrix, the upper n1 x n1 part contains distances between objects of type 1 the lower n2 x n2 part contains distances between objects of type 2 |

`n1` |
numbers of objects of type 1 |

`n2` |
numbers of objects of type 2 |

`w` |
(optional) weights of the objects (length n1+n2) |

`B` |
number of permutations to generate |

`alternative` |
alternative hypothesis ("less" to test H0:Colocalization ) |

`returnSample` |
return sampled null distribution |

`parallel` |
Logical. Should we use parallel computing? |

`...` |
additional arguments for mclapply |

a list with the p.value, the observed weighted mean of the cNN-distances, alternative and (if returnSample) the simulated null dist

Fabian Scheipl

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