3. Sparsity by Quadratic Penalties- This package fits classical sparse regression models with efficient active set algorithms by solving quadratic problems. Also provides a few methods for model selection purpose (cross-validation, stability selection).
4. heplots: Visualizing Multivariate Tests- Visualizing Tests in Multivariate Linear Models: The heplots package provides functions for representing sums-of-squares-and-products matrices for linear hypotheses and for error using ellipses (in two dimensions) and ellipsoids (in three dimensions).
Development Status : 5 - Production/Stable [Filter]
Topic : Machine Learning : Regularized and Shrinkage Methods [Filter]
Topic : Multivariate Statistics : Linear Models [Filter]
Registered: 2007-07-07 15:13
8. desiRe- desiRe allows the computation and interactive specification of desirability functions of Harrington- and Derringer/Suich-type. Related density and distribution functions, optimization procedures and several different types of charts are provided.
10. Generalized ridge trace plots- The genridge package introduces generalizations of the standard univariate ridge trace plot used in ridge regression and related methods. These graphical methods show both bias and precision.
11. Hierarchical Generalized Linear Models- The aim of the project is to develop a series of packages, including the hglm package, which implement the estimation algorithm of different random effects models based on the hierarchical likelihood theory.