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FlexReg  

Regression Models for Bounded Continuous and Discrete Responses
View on CRAN: Click here


Download and install FlexReg package within the R console
Install from CRAN:
install.packages("FlexReg")

Install from Github:
library("remotes")
install_github("cran/FlexReg")

Install by package version:
library("remotes")
install_version("FlexReg", "1.3.0")



Attach the package and use:
library("FlexReg")
Maintained by
Roberto Ascari
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-05
Latest Update: 2022-09-16
Description:
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.
How to cite:
Roberto Ascari (2020). FlexReg: Regression Models for Bounded Continuous and Discrete Responses. R package version 1.3.0, https://cran.r-project.org/web/packages/FlexReg. Accessed 21 Nov. 2024.
Previous versions and publish date:
1.0 (2020-11-05 09:20), 1.1 (2022-01-17 17:52), 1.2 (2022-09-16 11:46)
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