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 R-Forge site.
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:
At the moment, the documentation is minimal but we hope to correct this in the near future.