glmie
swMATH ID:  13249 
Software Authors:  Nickisch, Hannes 
Description:  Glmie: generalised linear models inference & estimation toolbox. The glmie toolbox contains functionality for estimation and inference in generalised linear models over continuousvalued variables. Besides a variety of penalised least squares solvers for estimation, it offers inference based on (convex) variational bounds, on expectation propagation and on factorial mean field. Scalable and efficient inference in fullyconnected undirected graphical models or Markov random fields with Gaussian and nonGaussian potentials is achieved by casting all the computations as matrix vector multiplications. We provide a wide choice of penalty functions for estimation, potential functions for inference and matrix classes with lazy evaluation for convenient modelling. We designed the glmie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files to be fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Large scale probabilistic classification as well as sparse linear modelling can be performed in a common algorithmical framework by the glmie toolkit. 
Homepage:  http://hannes.nickisch.org/code/glmie/doc/index.html 
Dependencies:  Matlab 
Keywords:  sparse linear models; generalised linear models; Bayesian inference; approximate inference; probabilistic regression and classification; penalised least squares estimation; lazy evaluation matrix class 
Related Software:  Matlab; LBFGSB; Octave; sparsenet; NumPy; SciPy; PyTables; Scikit; LibDAI; Libra; MLPACK; Python; ProSper 
Cited in:  0 Documents 
Standard Articles
1 Publication describing the Software  Year 

Glmie: generalised linear models inference \& estimation toolbox Nickisch, Hannes 
2012
