Software

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

Package Description Links
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, cycling and swimming data GitHub
waldi Location-adjusted Wald statistics GitHub

cranly directives network for my R packages

Below, I am using my R package cranly to quickly build the directives network for my R packages.

library("magrittr")
library("cranly")
clean_CRAN_db() %>%
    build_network() %>%
    plot(author = "Ioannis Kosmidis", legend = FALSE, width = "100%")