A particular focus of my work is the development of efficient, in terms of computational complexity and implementation, algorithms for applying the methods I develop to prominent data-analytic scenarios. This page lists the corresponding open-source software I have (co-)developed and (co-)maintain for that purpose.

R packages newspaper

betareg Beta regression [CRAN] [RForge]
brglm Bias reduction for binomial-response generalized linear models [CRAN] [RForge]
brglm2 Explicit and implicit methods for bias reduction in generalized linear models [CRAN] [GitHub]
cranly Package directives and collaboration networks in CRAN [CRAN] [GitHub]
brRasch Maximum likelihood and bias reduction for fixed-effects Rasch models [GitHub]
enrichwith Methods to enrich various R objects with extra components [CRAN] [GitHub]
PlackettLuce Plackett-Luce models [CRAN] [GitHub]
profileModel Tools for profiling inference functions for various model classes [CRAN] [RForge]
trackeR Infrastructure for running and cycling data from GPS-enabled tracking devices [CRAN] [GitHub]
trackeRapp Shiny interface for the analysis of running and cycling data [GitHub]
waldi Location-adjusted Wald statistics [GitHub]

cranly directives network for my R packages