R2_bayes

an object of class <code>`flexreg`</code>, usually the result of <code><a rd-options="" href="/link/flexreg?package=FlexReg&version=1.1" data-mini-rdoc="FlexReg::flexreg">flexreg</a></code> or <code><a rd-options="" href="/link/flexreg_binom?package=FlexReg&version=1.1" data-mini-rdoc="FlexReg::flexreg_binom">flexreg_binom</a></code>.

model

Bayesian version of R-squared for flexible regression models for continuous bounded or binomial data.

Functions to fit regression models for bounded responses (e.g., proportions and rates) and binomial data. Available models are the flexible beta (Migliorati, S., Di Brisco, A. M., Ongaro, A. (2018) <doi:10.1214/17-BA1079>), the variance-inflated beta (Di Brisco, A. M., Migliorati, S., Ongaro, A. (2020) <doi:10.1177/1471082X18821213>), the beta (Ferrari, S.L.P., and Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), the flexible beta-binomial (Ascari, R. and Migliorati, S. (2021) <doi:10.1002/sim.9005>), the beta-binomial, and the binomial one. Inference is dealt with a Bayesian approach based on the Hamiltonian Monte Carlo (HMC) algorithm (Gelman, A.; Carlin, J. B.; Stern, H. S. and Rubin, D. B. (2014) <doi:10.1201/b16018>). Besides, functions to compute residuals, posterior predictives, goodness-of-fit measures, convergence diagnostics, and graphical representations are provided.

Roberto Ascari

FlexReg

Regression Models for Bounded Responses

R2_bayes function

<dl><dt>model</dt>
<dd>an object of class <code>`flexreg`</code>, usually the result of <code>flexreg</code> or <code>flexreg_binom</code>.</dd></dl>

Arguments

Bayesian R-squared for flexreg Objects — R2_bayes

<dl>

<dt>model</dt>
<dd>an object of class <code>`flexreg`</code>, usually the result of <code>flexreg</code> or <code>flexreg_binom</code>.</dd>

</dl>

R2_bayes: Bayesian R-squared for flexreg Objects

Description

Usage

Arguments

Details

References

Examples