PymaBandits contains python and matlab implementations of algorithms for multi-armed bandit problems. The code has been written with Aurélien Garivier and Emilie Kaufmann and was used to perfom the simulations in

PymaBandits can be downloaded here.

Last edited 14 nov. 2018

Wapiti is a very fast CRF toolkit (written in C++) for segmenting and labeling items and sequence data written and maintained by Thomas Lavergne; Wapiti was developed within the CroTAL project.

Wapiti's implementation is described in

  • T. Lavergne, O. Cappé, and F. Yvon. Practical Very Large Scale CRFs. In Proc. 48th Annual Meeting Association for Computational Linguistics (ACL), pages 504-513, Uppsala, Sweden, July 2010.

and is based, partly, on

Wapiti is also available from the public evaluation site MLcomp and its performance appears to be very good on the SequenceTagging tasks (best program from the repository on 5 of the 16 datasets as of August 2010).

Last edited 5 juil. 2018

OnlineHMM contains the source code of MATLAB routines implementing the online Expectation-Maximization algorithm for the 'Markov chain in noise' HMM. It is available on the Journal of Computational and Graphical Statistics web site as the supplementary material of

Last edited 5 juil. 2018

OnlineEM contains the MATLAB/OCTAVE routines implementing the online Expectation-Maximization algorithm used for the numerical simulations presented in

Last edited 5 juil. 2018

CosmoPMC is a C-written environment for running adaptive population Monte Carlo for cosmology applications. CosmoPMC supports parallelism using MPI. It was written mostly by Martin Kilbinger, Karim Benabed and Simon Prunet for the ECOSSTAT project. Related papers are

Last edited 5 juil. 2018

Ihmm are the MATLAB/OCTAVE functions that where used for some of the simulations featured in the book Inference in Hidden Markov Models (Cappé, Rydén and Moulines - Springer, 2005), in particular for Kalman smoothing and (particle) resampling.

Currently available code includes functions for implementing

  • Kalman filtering and smoothing (with all three forms of smoothing: RTS, disturbance and Backward Information Recursion) for general (non-stationary) linear state-space models.
  • Resampling in a matlab efficient way (for multinomial, stratified, systematic and residual resampling).
Last edited 5 sept. 2012

CT/RJ-mix implements transdimensional Markov Chain Monte Carlo (MCMC) for inference in (scalar) Gaussian mixture models, with unknown number of components. Two methods are implemented: Reversible Jump (RJ) MCMC for rj_mix and Continuous Time (CT) for ct_mix

This is the C code that was used to produce the figures in Section 4 of

O. Cappé, C. Robert and T. Rydén. Reversible jump, birth-and-death and more general continuous time Markov chain Monte Carlo samplers. Journal of the Royal Statistical Society: Series B (Statistical Methodology), Volume 65, Issue 3, pages 679-700, 2003.

Please see this page for more information.

Last edited 5 sept. 2012

H2m is a set of MATLAB/OCTAVE functions for the EM estimation of mixture and hidden Markov models. h2m includes functions for Poisson and negative binomial models in addition to the multivariate Gaussian ones.

These functions (together with the corresponding documentation) are available as gz-compressed unix archive and PC zip file.

For more information please take a look at HTML documentation for H2m or the Pdf documentation

Last edited 5 sept. 2012

Env contains a set of MATLAB functions that implement the spectral envelope estimation methods described in

M. Campedel-Oudot, O. Cappé, and E. Moulines. Estimation of the spectral envelope of voiced sounds using a penalized likelihood approach. IEEE Trans. Speech Audio Process., 9(5):469-481, July 2001.

The gz-compressed unix archive also contains the signal and results shown in section IV.D of the paper.

Last edited 5 sept. 2012

Dcv is a set of MATLAB functions for testing various maximum likelihood and Bayesian blind deconvolution/estimation procedures in the case of discrete input signals. These functions (together with the corresponding documentation) are available as a compressed unix archive. For more information please see:

Last edited 5 sept. 2012