FD: Measuring functional diversity (FD) from multiple traits, and other tools for functional ecology
Version 1.0-12

FD is a package to compute different multidimensional FD indices. It implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances. It also contains other useful tools for functional ecology.

Browse man pages Browse package API and functions Browse package files

AuthorEtienne Lalibert, Pierre Legendre, Bill Shipley
Date of publication2014-08-19 13:42:17
MaintainerEtienne Lalibert <etiennelaliberte@gmail.com>
LicenseGPL-2
Version1.0-12
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("FD")

Man pages

dbFD: Distance-Based Functional Diversity Indices
dummy: Dummy Functional Trait Dataset
fdisp: Functional Dispersion
FD-package: Measuring Functional Diversity from Multiple Traits, and...
functcomp: Functional Composition
gowdis: Gower Dissimilarity
mahaldis: Mahalanobis Distance
maxent: Estimating Probabilities via Maximum Entropy: Improved...
maxent.test: Inferential Permutation Tests for Maximum Entropy Models
simul.dbFD: Simulations to Explore Relationships Between Functional...
tussock: Functional Composition of Short-Tussock Grasslands

Functions

FD Man page
FD-package Man page
dbFD Man page
dummy Man page
fdisp Man page
functcomp Man page
gowdis Man page
mahaldis Man page Source code
maxent Man page Source code
maxent.test Man page Source code
simul.dbFD Man page
tussock Man page

Files

inst
inst/CITATION
inst/NEWS
src
src/itscale5.f
src/gowdis.c
NAMESPACE
data
data/dummy.rda
data/tussock.rda
R
R/dbFD.R
R/functcomp.R
R/simul.dbFD.R
R/maxent.R
R/gowdis.R
R/fdisp.R
R/maxent.test.R
R/mahaldis.R
MD5
DESCRIPTION
man
man/functcomp.Rd
man/fdisp.Rd
man/maxent.Rd
man/tussock.Rd
man/FD-package.Rd
man/dbFD.Rd
man/mahaldis.Rd
man/simul.dbFD.Rd
man/gowdis.Rd
man/dummy.Rd
man/maxent.test.Rd
FD documentation built on May 19, 2017, 10:20 a.m.