Adrien Taudiere, Cyrille Violle with contribution by Francois Munoz
Detect and quantify community assembly processes using trait values of individuals or populations, the T-statistics and other metrics, and dedicated null models.

e1071, rasterVis, hypervolume, FD, geometry, vegan
lattice, spacodiR, entropart, fBasics, picante, mice, knitr

Adrien Taudiere [aut, cre], Cyrille Violle [aut] with contribution by Francois Munoz [contr]
Detect and quantify community assembly processes using trait values of individuals or populations, the T-statistics (Violle et al. (2012) <doi:10.1016/j.tree.2011.11.014>) and other metrics, and dedicated null models described in Taudiere & Violle (2016) <doi:10.1111/ecog.01433>.

c(person(given = "Adrien",
family = "Taudiere",
role = c("aut", "cre"),
email = "adrien.taudiere@tutanota.com",
comment = c(ORCID = "0000-0003-1088-1182")),
person(given = "Cyrille",
family = "Violle",
role = "aut",
comment = c(ORCID = "0000-0002-2471-9226")),
person(given = "François",
family = "Munoz",
role = "ctb",
comment = c(ORCID = "0000-0001-8776-4705"))
)
lattice, entropart, fBasics, picante, mice, knitr

Formal psychological models, independently-replicated data sets against which to test them, and simulation archives.

Formal Psychological Models of Categorization and Learning
Andy Wills, Lenard Dome, Charlotte Edmunds, Garrett Honke, Angus Inkster, Rene Schegelmilch, Stuart Spicer
Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.

Andy Wills, Lenard Dome, Charlotte Edmunds, Garrett Honke, Angus Inkster, René Schlegelmilch, Stuart Spicer
Rcpp (>= 0.12.6), doParallel, foreach, tidyr, dplyr

Rcpp (>= 1.0.0), doParallel, foreach, tidyr, dplyr

Case-control And Tdt Meta-Analysis Package
catmap is an R package that conducts fixed-effects (inverse variance) and random-effects (DerSimonian and Laird, 1986) meta-analyses of case-control or family-based (TDT) genetic data; in addition, it performs meta-analyses combining these two types of study designs.  The fixed-effects model was first described by Kazeem and Farrell (2005); the random-effects model is described in Nicodemus (submitted).}