laser implements maximum likelihood methods based on the birth-death
process to test whether diversification rates have changed over time and whether rates vary among lineages.

Likelihood Analysis of Speciation/Extinction Rates from
Phylogenies
laser implements maximum likelihood methods based on the
birth-death process to test whether diversification rates have
changed over time and whether rates vary among lineages.

Lasso-Zero for (High-Dimensional) Linear Regression
Model selection for the (possibly high-dimensional) linear regression model
with Lasso-Zero, an L1-based methodology relying on the repeated use of noise
dictionaries, as described by Descloux, P. and Sardy, S. (2018) <arXiv:1805.05133>.

Justin Lokhorst, Bill Venables and
Berwin Turlach <berwin@maths.uwa.edu.au>; first port to R: Martin Maechler
Routines and documentation for solving regression problems
while imposing an L1 constraint on the estimates, based on
the algorithm of Osborne et al. (1998)

Justin Lokhorst, Bill Venables and Berwin Turlach;
port to R, tests etc: Martin Maechler <maechler@stat.math.ethz.ch>

Justin Lokhorst, Bill Venables and Berwin Turlach; port to R,
tests etc: Martin Maechler <maechler@stat.math.ethz.ch>
Routines and documentation for solving regression problems
while imposing an L1 constraint on the estimates, based on the
algorithm of Osborne et al. (1998)

Routines and documentation for solving regression problems
while imposing an L1 constraint on the estimates, based on
the algorithm of Osborne et al. (1998).

Nonparametric P-Value Estimation for Predictors in Lasso
The purpose of this package is to estimate p-values for predictors x against target variable y in lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic. This is based on the assumption that predictors that (first) become active earlier tend to be more significant. Null distribution for each predictor is computed analytically under approximation, which aims at efficiency and accuracy for small p-values.