hilldiss: Hill numbers-based dissimilarity

In hilldiv3: Integral Analysis of Diversity Based on Hill Numbers

Hill numbers-based dissimilarity

Description

Compute overall (multi-sample) dissimilarity metrics from the Hill-number beta diversity following Chiu et al. (2014). These are the complements of the similarities returned by hillsim().

Usage

hilldiss(
  data,
  q = c(0, 1, 2),
  metric = c("S", "C", "U", "V"),
  tree = NULL,
  dist = NULL,
  tau = NULL,
  type = c("auto", "neutral", "phylogenetic", "functional"),
  out = c("tibble", "matrix")
)

Arguments

data	A count table (taxa x samples) or a supported object; a single sample is not meaningful for partitioning.
q	Numeric vector of diversity orders (>= 0). Defaults to c(0, 1, 2) (richness, Shannon, Simpson).
metric	Dissimilarity metric(s) to return, any of "S", "C", "U", "V". Defaults to all four.
tree	A phylogenetic tree of class phylo whose tip labels match the taxa in data.
dist	A functional distance matrix (or dist) over the taxa.
tau	Optional functional distance threshold. Defaults to max(dist).
type	Diversity type: "auto" (default) infers it from the inputs (counts only -> neutral, +tree -> phylogenetic, +dist -> functional); an explicit "neutral", "phylogenetic" or "functional" asserts the type and is validated against the inputs (e.g. "phylogenetic" requires a tree; "neutral" ignores any tree/dist carried by the object).
out	Output shape: "tibble" (default) returns a long-format data.frame with columns q, metric, value; "matrix" returns the legacy matrix (orders in rows, metrics in columns, dropped to a vector for a single metric).

Value

A long-format data.frame of class hill_dissimilarity (default, with a plot() method), or a matrix/vector of dissimilarities when out = "matrix".

See Also

hillsim(), hillpair(), hillpart()

Examples

counts <- matrix(c(10, 0, 5, 2, 8, 1), nrow = 3,
                 dimnames = list(c("t1", "t2", "t3"), c("s1", "s2")))
hilldiss(counts)
plot(hilldiss(counts))

hilldiv3 documentation built on Oct. 6, 2026, 5:06 p.m.