Karline Soetaert <karline.soetaert@nioz.nl>,
Dick van Oevelen<dick.vanoevelen@nioz.nl>

Linear Inverse Model Examples and Solution Methods
Functions that read and solve linear inverse problems (food web problems, linear programming problems).
These problems find solutions to linear or quadratic functions:
min or max (f(x)), where f(x) = ||Ax-b||^2 or f(x) = sum(ai*xi)
subject to equality constraints Ex=f and inequality constraints Gx>=h.

Yannick Baraud, Christophe Giraud, Sylvie Huet
LINselect allows to estimate the mean of a Gaussian vector, by choosing among a large collection of estimators. In particular it solves the problem of variable selection by choosing the best predictor among  predictors emanating from different methods as lasso, elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
mvtnorm, elasticnet, MASS, randomForest, pls, gtools

Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators. In particular it solves the problem of variable selection by choosing the best predictor among  predictors emanating from different methods as lasso, elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
mvtnorm, elasticnet, MASS, randomForest, pls, gtools, stats

Orphaned on 2018-06-09 as maintainer has retired and
her email address now bounces.

Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators,
following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) <doi:10.1214/13-AIHP539>.
In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso,
elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.

Longest Increasing Subsequence Independence Test
Jesus Garcia and Veronica Andrea Gonzalez Lopez
calculate the pvalue for the two samples L.I.S
independence test (for continuous random variables).