logicals, integers, doubles, characters and factors as well as
many elementwise and summary functions. Many fast algorithmic
operations such as 'match' and 'order' support interactive data
exploration and manipulation and optionally leverage caching.

Package 'bit64' provides serializable S3 atomic 64bit (signed) integers
that can be used in vectors, matrices, arrays and data.frames. Methods are
available for coercion from and to logicals, integers, doubles, characters
and factors as well as many elementwise and summary functions. Many fast
algorithmic operations such as 'match' and 'order' support interactive data

Depends: R (>= 3.0.1), bit (>= 1.1-12), utils, methods, stats

Title: A S3 Class for Vectors of 64bit Integers

Package 'bit64' provides serializable S3 atomic 64bit (signed) integers.
These are useful for handling database keys and exact counting in +-2^63.
WARNING: do not use them as replacement for 32bit integers, integer64 are not
supported for subscripting by R-core and they have different semantics when
combined with double, e.g. integer64 + double => integer64.
Class integer64 can be used in vectors, matrices, arrays and data.frames.
Methods are available for coercion from and to logicals, integers, doubles,
characters and factors as well as many elementwise and summary functions.
Many fast algorithmic operations such as 'match' and 'order' support inter-
active data exploration and manipulation and optionally leverage caching.

Author: Jens Oehlschlägel [aut, cre], Leonardo Silvestri [ctb]
Depends: R (>= 3.0.1), bit (>= 4.0.0), utils, methods, stats

Title: Bayesian Integrative Models of Trait Evolution
Authors@R: c(person("Theo", "Gaboriau", role = c("aut", "cre"),
person("Anna", "Kostikova", role = "aut",
person("Daniele", "Silvestro", role = "aut",
person("Sacha", "Laurent", role = "crt",
person("Martha", "Serrano", role = "crt",
person("Glenn", "Litsios", role = "crt",
person("Nicolas", "Salamin", role = "aut",
Description: Contains the JIVE (joint inter and intra-specific model of variance evolution) model and other Bayesian models aimed at understanding trait evolution. The goal of the package is to join phylogenetic comparative models (PCM) that tend to integrate various type of data (individual observations, environmental data, fossil data) into a hierarchical Bayesian framework. It contains various PCMs as well as functions to join those models into a hierarchical Bayesian framework in a flexible and user friendly way. It contains various Markov chain Monte-Carlo (MCMC) algorithms, methods for model comparison and many plotting function for pre- and post-processing data visualization. Finally, this package integrates functions allowing bridges between 'R' and the 'BEAST2' implementations of PCMs. Kostikova A, Silvestro D, Pearman PB, Salamin N (2016) <doi:10.1093/sysbio/syw010>. Gaboriau T, Mendes FK, Joly S, Silvestro D, Salamin N (in prep).
Imports: ape, MASS, phytools, coda, sm, vioplot, xml2