Skip to contents

Calculate the dissimilarity coeficient

Source: R/estimate_dissimilarity_coefficient.R
estimate_dissimilarity_coefficient.Rd

Calculate the dissimilarity coeficient

Usage

estimate_dissimilarity_coefficient(
  data_source_dc,
  dissimilarity_coefficient = "chord",
  verbose = FALSE
)

Arguments

data_source_dc

Data.frame with taxons as columns

dissimilarity_coefficient

Character. Dissimilarity coefficient. Type of calculation of differences between Working Units. See vegan::vegdist for more details.

  • "euc" - Euclidean distance

  • "euc.sd" - Standardised Euclidean distance

  • "chord" - Chord distance

  • "chisq" - Chi-squared coefficient

  • "gower" - Gower's distance

  • "bray" - Bray-Curtis distance

verbose

Logical. If TRUE, function will output messages about internal processes

Details

Five in-built dissimilarity coefficients are available:

  • Euclidean distance (dissimilarity_coefficient = "euc")

  • standardised Euclidean distance (dissimilarity_coefficient = "euc.sd")

  • Chord distance (dissimilarity_coefficient = "chord")

  • Chi-squared coefficient (dissimilarity_coefficient = "chisq")

  • Gower's distance (dissimilarity_coefficient = "gower")

  • Bray-Curtis distance (dissimilarity_coefficient = "bray")

The choice of dissimilarity_coefficient depends on the type of assemblage data. In addition, RoC between WUs be calculated using every consecutive WU (only_subsequent = FALSE), or alternatively, calculation of RoC can be restricted to only directly adjacent WUs (only_subsequent = TRUE). Using the former increases the number of samples for which RoC can be calculated within a sequence, which varies in terms of sample resolution, but may still introduce biases related to the RoC estimation as a result of the varying inter-sample distances.

See also

vegan::vegdist()