| 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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