Latent Budget Analysis for Compositional Data
Enio G. Jelihovschi <eniojelihovs@gmail.com>
Ivan Bezerra Allaman <ivanalaman@gmail.com>
R (>= 3.1.2), MASS, alabama, plotrix, ca
Latent budget analysis is a method for the analysis of a two-way contingency table with an exploratory variable and a response variable. It is specially designed for compositional data.

Enio G. Jelihovschi <eniojelihovs@gmail.com>  and
Ivan Bezerra Allaman <ivanalaman@gmail.com>

R (>= 3.1.0), MASS, alabama, plotrix, scatterplot3d, rgl
Latent budget analysis is a method for the analysis of a two-way
contingency table with an exploratory variable and a response variable. It is
specially designed for compositional data.

Enio G. Jelihovschi <eniojelihovs@gmail.com>  and
Ivan Bezerra Allaman <iballaman@uesc.br>

c(person("Antonio", "Coppola", role = c("aut", "cre", "cph"), email = "acoppola@college.harvard.edu"),
person("Brandon", "Stewart", role = c("aut", "cph")),
person("Naoaki", "Okazaki", role = c("aut", "cph")),
person("David", "Ardia", role = c("ctb", "cph")),
person("Dirk", "Eddelbuettel", role = c("ctb", "cph")),
person("Katharine", "Mullen", role = c("ctb", "cph")),
person("Jorge", "Nocedal", role = c("ctb", "cph")))
A wrapper built around the libLBFGS optimization library by Naoaki Okazaki. The lbfgs package implements both the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) and the Orthant-Wise Quasi-Newton Limited-Memory (OWL-QN) optimization algorithms. The L-BFGS algorithm solves the problem of minimizing an objective, given its gradient, by iteratively computing approximations of the inverse Hessian matrix. The OWL-QN algorithm finds the optimum of an objective plus the L1-norm of the problem's parameters. The package offers a fast and memory-efficient implementation of these optimization routines, which is particularly suited for high-dimensional problems.
Antonio Coppola [aut, cre, cph],
Brandon Stewart [aut, cph],
Naoaki Okazaki [aut, cph],
David Ardia [ctb, cph],
Dirk Eddelbuettel [ctb, cph],
Katharine Mullen [ctb, cph],
Jorge Nocedal [ctb, cph]