CladisticInfo() calculates the cladistic (phylogenetic) information content of a phylogenetic object, sensu Thorley et al. (1998).

CladisticInfo(x)

PhylogeneticInfo(x)

# S3 method for phylo
CladisticInfo(x)

# S3 method for Splits
CladisticInfo(x)

# S3 method for list
CladisticInfo(x)

# S3 method for multiPhylo
CladisticInfo(x)

PhylogeneticInformation(x)

CladisticInformation(x)

Arguments

x

Tree of class phylo, or a list thereof.

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(), Stemwardness, TotalCopheneticIndex()