HqzBeta {entropart} | R Documentation |
Similarity-based beta entropy of a community
Description
Calculates the similarity-based beta entropy of order q
of a community belonging to a metacommunity.
Usage
HqzBeta(NorP, NorPexp = NULL, q = 1, Z = diag(length(NorP)), ...)
bcHqzBeta(Ns, Nexp = NULL, q = 1, Z = diag(length(Ns)), Correction = "Best",
CheckArguments = TRUE)
## S3 method for class 'ProbaVector'
HqzBeta(NorP, NorPexp = NULL, q = 1, Z = diag(length(NorP)),
..., CheckArguments = TRUE, Ps = NULL, Pexp = NULL)
## S3 method for class 'AbdVector'
HqzBeta(NorP, NorPexp = NULL, q = 1, Z = diag(length(NorP)), Correction = "Best",
..., CheckArguments = TRUE, Ns = NULL, Nexp = NULL)
## S3 method for class 'integer'
HqzBeta(NorP, NorPexp = NULL, q = 1, Z = diag(length(NorP)), Correction = "Best",
..., CheckArguments = TRUE, Ns = NULL, Nexp = NULL)
## S3 method for class 'numeric'
HqzBeta(NorP, NorPexp = NULL, q = 1, Z = diag(length(NorP)), Correction = "Best",
..., CheckArguments = TRUE, Ps = NULL, Ns = NULL, Pexp = NULL, Nexp = NULL)
Arguments
Ps |
The probability vector of species of the community. |
Pexp |
The probability vector of species of the metacommunity. |
Ns |
A numeric vector containing species abundances of the community. |
Nexp |
A numeric vector containing species abundances of the metacommunity. |
NorP |
A numeric vector, an integer vector, an abundance vector ( |
NorPexp |
A numeric vector, an integer vector, an abundance vector ( |
q |
A number, the order of diversity. Default is 1. |
Z |
A relatedness matrix, i.e. a square matrix whose terms are all positive, strictly positive on the diagonal. Generally, the matrix is a similarity matrix, i.e. the diagonal terms equal 1 and other terms are between 0 and 1. Default is the identity matrix to calculate neutral entropy. |
Correction |
A string containing one of the possible corrections: currently, no correction is available so |
... |
Additional arguments. Unused. |
CheckArguments |
Logical; if |
Details
The derivation of similarity-based beta entropy can be found in Marcon et al. (2014).
Bias correction requires the number of individuals.
Note that beta entropy value is related to alpha entropy (if q
is not 1) and cannot be compared accross communities (Jost, 2007). Beta entropy of a community is not meaningful in general, do rather calculate the BetaDiversity
of the metacommunity.
The functions are designed to be used as simply as possible. HqzBeta
is a generic method. If its first argument is an abundance vector, an integer vector or a numeric vector which does not sum to 1, the bias corrected function bcHqzBeta
is called. Explicit calls to bcHqzBeta
(with bias correction) or to HqzBeta.ProbaVector
(without correction) are possible to avoid ambiguity. The .integer
and .numeric
methods accept Ps
or Ns
arguments instead of NorP
for backward compatibility.
Value
A named number equal to the calculated entropy. The name is that of the bias correction used.
References
Jost (2007), Partitioning diversity into independent alpha and beta components. Ecology 88(10): 2427-2439.
Marcon, E., Zhang, Z. and Herault, B. (2014). The decomposition of similarity-based diversity and its bias correction. HAL hal-00989454(version 3).
Examples
# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
data(Paracou618)
# Ps is the vector of probabilities
Ps <- as.ProbaVector(Paracou618.MC$Ps)
# Probability distribution of the first plot
Ps1 <- as.ProbaVector(Paracou618.MC$Psi[, 1])
# Prepare the similarity matrix
DistanceMatrix <- as.matrix(Paracou618.dist)
# Similarity can be 1 minus normalized distances between species
Z <- 1 - DistanceMatrix/max(DistanceMatrix)
# Divergence of order 2 between plot 1 and the whole forest
HqzBeta(Ps1, Ps, q=2, Z)