Imports: RcppArmadillo, quadprog, stats, dendextend, RColorBrewer,

Author: The students of the `Advanced R Programming Course' Hannah
Frick, Ivan Kondofersky, Oliver S. Kuehnle, Christian
Lindenlaub, Georg Pfundstein, Matthias Speidel, Martin
Spindler, Ariane Straub, Florian Wickler, Katharina Zink under
the supervision of Manuel Eugster and Torsten Hothorn
Description: High-dimensional additive models as introduced by Meier,
Depends: grplasso, splines, lattice, rgl

Packaged: 2013-02-08 18:44:48 UTC; mjaeugster

Packaged: 2013-05-13 17:37:45 UTC; mjaeugster

Title: Learning graphical models with hubs
Maintainer: Kean Ming Tan <keanming@uw.edu>
Description: Implements the hub graphical lasso and hub covariance graph proposal by Tan et al. (2014).
Packaged: 2014-03-29 01:47:58 UTC; keanmingtan

Description: Implements the hub graphical lasso and hub covariance graph proposal by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). Learning graphical models with hubs.  arXiv.org/pdf/1402.7349.pdf.
Packaged: 2014-05-04 20:02:49 UTC; keanmingtan

Description: Implements the hub graphical lasso and hub covariance graph proposal by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). Learning graphical models with hubs. To appear in Journal of Machine Learning Research. arXiv.org/pdf/1402.7349.pdf.
Packaged: 2014-08-09 22:11:27 UTC; keanmingtan

Title: Learning Graphical Models with Hubs
Maintainer: Kean Ming Tan <keanming@umich.edu>
Description: Implements the hub graphical lasso and hub covariance graph proposal by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). Learning graphical models with hubs. Journal of Machine Learning Research 15(Oct):3297-3331.
Packaged: 2022-05-13 04:58:47 UTC; keanmingtan

Title: hglm is used to fit hierarchical generalized linear models.
Description: The hglm package is used to fit hierarchical generalized
linear models. It can be used for linear mixed models and
generalized linear mixed models with random effects for a
variety of links and a variety of distributions for both the
outcomes and the random effects. Fixed effects can also be
fitted in the dispersion part of the mean model.