person("Hussein", "Hazimeh", email = "hazimeh@mit.edu", role = c("aut", "cre")),
person("Rahul", "Mazumder", email = "rahulmaz@mit.edu", role = "aut"),
person("Tim", "Nonet", email = "tim.nonet@gmail.com", role = "aut"))
Description: Highly optimized toolkit for approximately solving L0-regularized learning problems (a.k.a. best subset selection).
For more details, check the paper by Hazimeh and Mazumder (2020);
Imports: Rcpp (>= 0.12.13), Matrix, methods, ggplot2, reshape2, MASS
Suggests: knitr, rmarkdown, testthat, pracma, raster, tilting

Suggests: knitr, rmarkdown, testthat, pracma, raster

Description: Fitting the regularization path of the L1-regularized multi-state models since they can exploit sparsity structure of input. Different tuning regularization parameter methods are provided. The cumulative hazard rate estimation and the transition probability predictions can be made from the fitted models.
Depends: Matrix (>= 1.2-10), MASS, mstate, colorspace

Description: L1 estimation for linear regression and random number generation for

Authors@R: c(person("Felipe", "Osorio", role = c("aut", "cre"), email = "felipe.osorios@usm.cl"),
person("Tymoteusz", "Wolodzko", role = "aut"))
Description: L1 estimation for linear regression, density, distribution function,
quantile function and random number generation for univariate and multivariate
Author: Felipe Osorio [aut, cre], Tymoteusz Wolodzko [aut]

c(person(given = "Felipe", family = "Osorio",
person(given = "Tymoteusz", family = "Wolodzko",
Author: Felipe Osorio [aut, cre] (<https://orcid.org/0000-0002-4675-5201>),

Author: Felipe Osorio [aut, cre] and Tymoteusz Wolodzko [aut]

Description: L1 estimation for linear regression using Barrodale and Roberts' method
density, distribution function, quantile function and random number generation
for univariate and multivariate Laplace distribution.

Authors@R: c(person("Dimitrios", "Bagkavos", role = c("aut", "cre"), email = "dimitrios.bagkavos@gmail.com") )
Description: Provides functions for the implementation of a density goodness-of-fit test, based on piecewise approximation of the L2 distance.