Title: Measuring functional diversity (FD) from multiple traits
Description: 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.
Packaged: Thu Apr 16 19:49:25 2009; etienne

Title: Measuring functional diversity (FD) from multiple traits, and
also consider species relative abundances. It also contains
other useful tools for functional ecology.

Title: Measuring Functional Diversity (FD) from Multiple Traits, and
Author: Etienne Lalibert�, Pierre Legendre, Bill Shipley
Description: Computes different multidimensional FD indices.  Implements a distance-based framework to measure FD that allows any number and type of functional traits, and can also consider species relative abundances.  Also contains other useful tools for functional ecology.

Description: 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.

Title: Multivariate Dependence with FDG Copulas
Description: FDG copulas are a class of copulas featuring an interesting balance between flexibility and tractability. This package provides tools to construct, calculate the pairwise dependence coefficients of, simulate from, and fit FDG copulas. The acronym FDG stands for 'one-Factor with Durante Generators', as an FDG copula is a one-factor copula -- that is, the variables are independent given a latent factor -- whose linking copulas belong to the Durante class of bivariate copulas (also referred to as exchangeable Marshall-Olkin or semilinear copulas).

Title: FDR-Control in Multiscale Change-Point Segmentation
Authors@R: c(person("Housen", "Li", role = c("aut", "cre"), email = "housen.li@outlook.com"),
person("Hannes", "Sieling", role = "aut", email = "hsielin@uni-goettingen.de"))
Description: Estimate step functions via multiscale inference with controlled false discovery rate (FDR). For details see H. Li, A. Munk and H. Sieling (2016) <doi:10.1214/16-EJS1131>.