dist.hamming and dist.logDet compute pairwise distances
for an object of class phyDat. dist.ml fits distances
for amino acid models.
Usage
dist.hamming(x, ratio = TRUE)
dist.logDet(x)
dist.ml(x, model="JC69",...)
Arguments
x
an object of class dist.logDet
ratio
compute uncorrected ('p') distance or character difference.
model
One of "JC69", "WAG", "JTT", "LG" or "Dayhoff"
...
Further arguments passed to or from other methods.
Value
an object of class dist
References
Lockhart, P. J., Steel, M. A., Hendy, M. D. and Penny, D. (1994)
Recovering evolutionary trees under a more realistic model of sequence
evolution. Molecular Biology and Evolution, 11, 605--602.
See Also
For more distance methods for nucleotide data see dist.dna