Bayesiangammareg - Double Generalized Gamma Regression Models
Fits double generalized Gamma regression models from a
Bayesian perspective, where both the mean and shape parameters
are modeled simultaneously using flexible link functions. The
methodology is based on Cepeda-Cuervo and Urdinola (2012)
<doi:10.1080/03610918.2011.600500> and extended in
Cepeda-Cuervo (2026), 'Double Generalized Linear Models:
Likelihood and Bayesian Methods' (ISBN: 9781041169970). The
package provides parameter estimation, model fitting, and model
comparison tools, including Akaike Information Criterion (AIC)
and Bayesian Information Criterion (BIC).
