Claddis (version 0.7.0)

calculate_WMPD: Calculate weighted mean pairwise distances

Description

Given distanceMatrices and taxonGroups objects calculates their weighted mean pairwise distances.

Usage

calculate_WMPD(distances, taxon_groups)

Value

A labelled vector of weighted mean pairwise distances.

Arguments

distances

An object of class distanceMatrices.

taxon_groups

An object of class taxonGroups.

Author

Graeme T. Lloyd

Details

Not all measures of disparity (morphological distance) require an ordination space. For example, the pariwise distances between taxa are themselves a disparity metric. However, due to variable amounts of missing data each pairwise distance should not necessarily be considered equal. Specifically, it could be argued that for a group of taxa the mean distance should be weighted by the number of characters that distance is based on, or more specifically the sum of the weights of those characters (e.g., Close et al. 2015).

This function takes the output from calculate_morphological_distances and a set of taxon groups and returns the weighted mean pairwise distance for those groups.

References

Close, R. A., Friedman, M., Lloyd, G. T. and Benson, R. B. J., 2015. Evidence for a mid-Jurassic adaptive radiation in mammals. Current Biology, 25, 2137-2142.

Examples

# Get morphological distances for the Day et al. (2016) data set:
distances <- calculate_morphological_distances(
  cladistic_matrix = day_2016,
  distance_metric = "mord",
  distance_transformation = "none"
)

# Build simple taxonomic groups for Day et al. (2016) data set:
taxon_groups <- list(nonBurnetiamorpha = c("Biarmosuchus_tener", "Hipposaurus_boonstrai",
  "Bullacephalus_jacksoni", "Pachydectes_elsi", "Niuksenitia_sukhonensis", "Ictidorhinus_martinsi",
  "RC_20", "Herpetoskylax_hopsoni"), Burnetiamorpha = c("Lemurosaurus_pricei", "Lobalopex_mordax",
  "Lophorhinus_willodenensis", "Proburnetia_viatkensis", "Lende_chiweta",
  "Paraburnetia_sneeubergensis", "Burnetia_mirabilis", "BP_1_7098"))

# Set class as taxonGroups:
class(taxon_groups) <- "taxonGroups"

# Calculate mean pairiwise distances:
calculate_MPD(distances, taxon_groups)

# Now calculate weighted mean pairwise distances:
calculate_WMPD(distances, taxon_groups)