| Projects on Google Code | Results 1 - 10 of 11 |
BEAST, Bayesian Evolutionary Analysis Sampling Trees, is a cross-platform program for Bayesian MCMC analysis of molecular sequences. It is orientated towards (strict and relaxed) molecular clock analyses. It can be used as a method of constructing phylogenies, but it is also intended for testing evo...
java,
MCMC,
molecular,
evolution,
bioinformatics,
phylogeny,
sequence,
bayesian,
phylogenetics,
beast,
coalescent
bugsParallel is a set of R functions for distributed computing with WinBUGS. BugsParallel:
* Has been successfully installed on MS Windows and Mac OS X platforms.
* Is a modified subset of the R2WinBUGS package.
* Uses the R package Rmpi to implement a network of Windows workstations.
...
A C library for doing 'decent' speed MCMC
=PyMC=
Bayesian estimation, particularly using Markov chain Monte Carlo (MCMC), is an increasingly relevant approach to statistical estimation. However, few statistical software packages implement MCMC samplers, and they are non-trivial to code by hand. PyMC is a python module that implements the...
A compiler for BLOG - Bayesian Logic. This compiler can convert BLOG models and query variables directly to C code. The generated C code uses MCMC inference (Gibbs sampling if possible) to generate the answer.
*BAli-Phy* is MCMC software developed by Ben Redelings with Marc Suchard for simultaneous Bayesian estimation of alignment and phylogeny (and other parameters). (See the paper and the Application Note.)
*BAli-Phy* can estimate phylogenetic trees from sequence data when the alignment is uncertain...
MCMC,
phylogeny,
multiple-sequence-alignment,
evolution,
inference,
statistics,
indel,
insertion,
deletion,
gap
moBayes provides a graphical user interface to analyze simple multi-scale occupancy models with the Markov chain Monte Carlo toolkit PyMC 0.9.2.
This project is aimed to collect all statistical models developed by the BayesFor association.
We encourage the participation of third part institutions, companies and people that share our desire to facilitate the dissemination of technical knowledge in the field of applied statistics.
This is a HIV Project.
RGS aims to be an R package for flexibly defining and fitting hierarchical Bayesian models by eventually defining custom samplers in either C or R, and obtaining simulators with good performances (e.g., compared with JAGS).
The typical RGS workflow would be the following:
# specify the hierarchi...