Forum: DirichletReg 0.6-0 on R-Forge
One central improvement was to implement all time-critical routines in C (called via .Call). In this version, log-likelihood and gradient functions are finally mostly calculated using compiled C code. While working on the transition from R to C, some routines were optimized for performance.
Another important feature was the implementation of a drop1 method for the models. This greatly eases backward-selection – add1 and finally something like a stepAIC method (as in MASS) are planned to automatize the process.
To expand the package with confidence (i.e., change stuff without breaking existing functions), there is a test-suite (right now for the common model) using the great package testthat, that checks results, etc.
A working paper was published and citation information was updated. The vignette is the working paper’s full code.
Maier, M. J. (2014). DirichletReg: Dirichlet Regression for Compositional Data in R. Research Report Series / Department of Statistics and Mathematics, 125. WU Vienna University of Economics and Business, Vienna. URL: http://epub.wu.ac.at/4077/
Finally, there have been lots and lots of small changes, fixes, etc.
Thanks for your interest and if you find any bugs or experience unexpected behavior, please don’t hesitate to contact me.
Marco J. Maier - 2014-12-12 11:25 -