FlexReg
Regression Models for Bounded Continuous and Discrete Responses
Functions to fit regression models for bounded continuous and discrete responses. In case of bounded continuous responses (e.g., proportions and rates), available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018)), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020)), the beta (Ferrari, S.L.P., Cribari-Neto, F. (2004)), and their augmented versions to handle the presence of zero/one values (Di Brisco, A. M., Migliorati, S. (2020)) are implemented. In case of bounded discrete responses (e.g., bounded counts, such as the number of successes in n trials), available models are the flexible beta-binomial (Ascari, R., Migliorati, S. (2021)), the beta-binomial, and the binomial are implemented. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2014)). Besides, functions to compute residuals, posterior predictives, goodness of fit measures, convergence diagnostics, and graphical representations are provided.
- Version1.3.0
- R version≥ 3.5.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release09/29/2023
Team
Roberto Ascari
Sonia Migliorati
Show author detailsRolesAuthorAgnese M. Di Brisco
Show author detailsRolesAuthor, MaintainerAndrea Ongaro
Show author detailsRolesAuthor
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- Imports8 packages
- Suggests1 package
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