CladisticInfo() calculates the cladistic (phylogenetic) information
content of a phylogenetic object, sensu Thorley et al. (1998).
Usage
CladisticInfo(x)
PhylogeneticInfo(x)
# S3 method for class 'phylo'
CladisticInfo(x)
# S3 method for class 'Splits'
CladisticInfo(x)
# S3 method for class 'list'
CladisticInfo(x)
# S3 method for class 'multiPhylo'
CladisticInfo(x)
PhylogeneticInformation(x)
CladisticInformation(x)Value
CladisticInfo() returns a numeric giving the cladistic information
content of the input tree(s), in bits.
If passed a Splits object, it returns the information content of each
split in turn.
Details
The CIC is the logarithm of the number of binary trees that include the specified topology. A base two logarithm gives an information content in bits.
The CIC was originally proposed by Rohlf (1982) , and formalised, with an information-theoretic justification, by Thorley et al. (1998) . Steel and Penny (2006) term the equivalent quantity "phylogenetic information content" in the context of individual characters.
The number of binary trees consistent with a cladogram provides a more satisfactory measure of the resolution of a tree than simply counting the number of edges resolved (Page 1992) .
References
Page RD (1992).
“Comments on the information content of classifications.”
Cladistics, 8(1), 87–95.
doi:10.1111/j.1096-0031.1992.tb00054.x
.
Rohlf FJ (1982).
“Consensus indices for comparing classifications.”
Mathematical Biosciences, 59(1), 131–144.
doi:10.1016/0025-5564(82)90112-2
.
Steel MA, Penny D (2006).
“Maximum parsimony and the phylogenetic information in multistate characters.”
In Albert VA (ed.), Parsimony, Phylogeny, and Genomics, 163–178.
Oxford University Press, Oxford.
Thorley JL, Wilkinson M, Charleston M (1998).
“The information content of consensus trees.”
In Rizzi A, Vichi M, Bock H (eds.), Advances in Data Science and Classification, 91–98.
Springer, Berlin.
ISBN 978-3-540-64641-9, doi:10.1007/978-3-642-72253-0
.
See also
Other tree information functions:
NRooted(),
TreesMatchingTree()
Other tree characterization functions:
Consensus(),
J1Index(),
Stemwardness,
TotalCopheneticIndex()