FlexReg1.4.2 package

Regression Models for Bounded Continuous and Discrete Responses

Beta

The Mean-Precision Parameterized Beta Distribution

BetaBin

The Beta-Binomial Distribution

convergence.diag.internal

internal function

convergence.diag

Convergence diagnostics

convergence.plot.internal

internal function

convergence.plot

Convergence plots

curve.density

Draw density plots

extract.pars

extract.pars

FB

The Flexible Beta Distribution

FBB

The Flexible Beta-Binomial Distribution

fit.model_2

internal function

fit.model_binom

internal function

flexreg_binom

Flexible Regression Models for Bounded Discrete Responses

FlexReg-package

The 'FlexReg' package.

flexreg

Flexible Regression Models for Bounded Continuous Responses

model_frame

Construct Design Matrices for flexreg Objects

model.matrix.flexreg

Construct Design Matrices for flexreg Objects

mu.chain.nd

mu.chain.nd

newdata.adjust

newdata.adjust

phi.chain.nd

phi.chain.nd

plot.flexreg_postpred

Plot Method for flexreg_postpred objects

plot.flexreg

Plot Method for flexreg Objects

posterior_predict.flexreg

Posterior Predictive Method for flexreg objects

posterior_predict

posterior_predict

predict_lambda.chain

predict_lambda.chain

predict_link

predict_link

predict_mu.chain

predict_mu.chain

predict_over

predict_over

predict_precision

predict_precision

predict_q.chain

predict_q.chain

predict_response

predict_response

predict_variance

predict_variance

predict.flexreg

Predict Method for flexreg Objects

print.flexreg

Print Methods for flexreg Objects

q0.chain.nd

q0.chain.nd

q01.chain.nd

q01.chain.nd

q1.chain.nd

q1.chain.nd

R2_bayes

Bayesian R-squared for flexreg Objects

R2Bayes_internal

internal function

rate_plot

rate_plot

residuals.flexreg

Residuals Method for flexreg Objects

summary.flexreg_postpred

Summary Method for flexreg_postpred objects

summary.flexreg

Methods for flexreg Objects

theta.chain.nd

theta.chain.nd

var.fun

var.fun

VIB

The Variance-Inflated Beta Distribution

WAIC_internal

internal function

WAIC

WAIC and LOO

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) <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., Cribari-Neto, F. (2004) <doi:10.1080/0266476042000214501>), and their augmented versions to handle the presence of zero/one values (Di Brisco, A. M., Migliorati, S. (2020) <doi:10.1002/sim.8406>) 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) <doi:10.1002/sim.9005>), 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) <doi:10.1201/b16018>). Besides, functions to compute residuals, posterior predictives, goodness of fit measures, convergence diagnostics, and graphical representations are provided.

  • Maintainer: Roberto Ascari
  • License: GPL (>= 2)
  • Last published: 2026-02-04