Provides functions for cobin and micobin regression models, a new family of generalized linear models for continuous proportional data (Y in the closed unit interval [0, 1]). It also includes an exact, efficient sampler for the Kolmogorov-Gamma random variable. For details, see Lee et al. (2026)
Cobin and micobin regression models are scalable and robust alternative to beta regression model for continuous proportional data. See the following paper for more details:
Lee, C. J., Dahl, B. K., Ovaskainen, O., Dunson, D. B. (2026). Scalable and robust regression models for continuous proportional data. Journal of the American Statistical Association, in press.
Preprint is available at https://arxiv.org/abs/2504.15269 as well as a journal version at https://doi.org/10.1080/01621459.2026.2626081.
A dedicated Github repository for reproducing the analysis in the paper is available at https://github.com/changwoo-lee/cobin-reproduce. This R package repository contains the functions for the cobin and micobin regression models, as well as sampler for Kolmogorov-Gamma random variables.
Install the package:
install.packages("cobin") # from CRAN
# or the development version from GitHub
# install.packages("devtools")
devtools::install_github("changwoo-lee/cobin")
Glossaries: GLM: generalized linear model; GLMM: generalized linear mixed model; GP: Gaussian process; NNGP: nearest neighbor Gaussian process; cobin: continuous binomial; micobin: mixture of continuous binomial;
Comparison of cobin and beta density
Comparison of micobin and beta density
Please see MMI data analysis code corresponding to the Section 5 of the paper(https://doi.org/10.1080/01621459.2026.2626081). More detailed examples TBA.
dcobin(x, theta, lambda): Density of
$\mathrm{cobin}(\theta, \lambda^{-1})$ at xrcobin(n, theta, lambda): Random variate generation from
$\mathrm{cobin}(\theta, \lambda^{-1})$dmicobin(x, theta, psi): Density of
$\mathrm{micobin}(\theta, \psi)$ at xrmicobin(n, theta, psi): Random variate generation from
$\mathrm{micobin}(\theta, \psi)$cobinreg(): fit Bayesian cobin GLM or GLMMmicobinreg(): fit Bayesian micobin GLM or GLMMcobinreg(): fit spatial cobin regressonmicobinreg(): fit Bayesian cobin GLM or GLMMqcb(), rcb(): quantile and random variate generation of
continuous BernoullidIH(): density of Irwin-Hall distributionbft(): $B(x) = \log((\exp(x)-1)/x)$, cumulant (log partition)
functionbftprime(): $B'(x) = 1/(1-\exp(-x))-1/x$, corresponding to inverse
of cobit link functionbftprimeprime(), bftprimeprimeprime(): $B''(x)$ and $B'''(x)$bftprimeinv(): inverse of $B'(x)$, corresponding to cobit link
functionVft(): $B''((B')^{-1}(\mu))$, variance function of cobincobinfamily(): a list of functions and expressions needed to fit
cobin GLMglm.cobin(): fit cobin GLM using iteratively reweighted least
squares (stats::glm.fit). Supports link functions “cobit”,
“logit”, “probit”, “cloglog”, “cauchit”.