For statistical and computational modelling, we mainly use R. For experiments, we mainly use javascript and html. R packages are hosted on CRAN and R-Forge, but we have recently started to use github.
DepmixS4 is written and maintained by Ingmar Visser and Maarten Speekenbrink and based on Ingmar’s earlier depmix package. DepmixS4 has an object-oriented design, providing a flexible interface to fit dependent mixture models with different observation models. Estimation is done by Expectation-Maximisation or numerical optimization of the likelihood using Rsolnp. The current stable release of depmixS4 can be found on CRAN. The latest (beta) version can be found on GitHub.
The Dynamic Lens Model (DLM, Speekenbrink & Shanks, 2010) is used to estimate cue utilization in MCPL tasks. Essentially, the model is a dynamic linear regression model (dlrm). Estimation relies on the Kalman filter/smoother and Expectation-Maximisation. The R package “dlrm” implements this and is hosted on R-Forge. It can be downloaded from this link. To install this package directly within R type:
install.packages("dlrm", repos="http://R-Forge.R-project.org")
At the moment, the documentation is minimal but we hope to correct this in the near future.