estimate_dissimilarity_coefficient: Calculate the dissimilarity coeficient

In HOPE-UIB-BIO/R-Ratepol-package: R-Ratepol: Estimating Rate of Change in Temporal Sequences

Calculate the dissimilarity coeficient

Description

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()

HOPE-UIB-BIO/R-Ratepol-package documentation built on March 6, 2024, 7:10 a.m.