FlexReg-package: The 'FlexReg' package.

In FlexReg: Regression Models for Bounded Continuous and Discrete Responses

The ‘FlexReg’ package.

Description

The FlexReg package provides functions and methods to implement several types of regression models for bounded continuous responses (e.g., proportions and rates) and bounded discrete responses (e.g., number of successes in n trials). Inferential statistical analysis is dealt with by a Bayesian estimation procedure based on the Hamiltonian Monte Carlo (HMC) algorithm through the rstan package.

References

Ascari, R., Migliorati, S. (2021). A new regression model for overdispersed binomial data accounting for outliers and an excess of zeros. Statistics in Medicine, 40(17), 3895–3914. doi:10.1002/sim.9005

Di Brisco, A. M., Migliorati, S. (2020). A new mixed-effects mixture model for constrained longitudinal data. Statistics in Medicine, 39(2), 129–145. doi:10.1002/sim.8406

Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020). Robustness against outliers: A new variance inflated regression model for proportions. Statistical Modelling, 20(3), 274–309. doi:10.1177/1471082X18821213

Ferrari, S.L.P., Cribari-Neto, F. (2004). Beta Regression for Modeling Rates and Proportions. Journal of Applied Statistics, 31(7), 799–815. doi:10.1080/0266476042000214501

Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018). A New Regression Model for Bounded Responses. Bayesian Analysis, 13(3), 845–872. doi:10.1214/17-BA1079

Stan Development Team (2020). RStan: the R interface to Stan. R package version 2.19.3. https://mc-stan.org

FlexReg documentation built on Sept. 29, 2023, 9:06 a.m.