print_glm_bayes_joint_binomial_suggestion: Generate Suggestions for Bayesian Joint Binomial GLM...

In catalytic: Tools for Applying Catalytic Priors in Statistical Modeling

Generate Suggestions for Bayesian Joint Binomial GLM Parameter Estimation

Description

This function provides suggestions for improving the parameter estimation process in Bayesian joint Binomial GLM modeling based on the diagnostic output from a Stan model. It evaluates the results and suggests adjustments to improve model fit and convergence.

Usage

print_glm_bayes_joint_binomial_suggestion(
  alpha,
  stan_iter,
  stan_sample_model,
  binomial_joint_theta,
  binomial_joint_alpha,
  binomial_tau_lower
)

Arguments

alpha	Numeric. The alpha parameter used in the prior distribution.
stan_iter	Integer. The number of iterations used in Stan sampling.
stan_sample_model	Stan model object containing sampling results.
binomial_joint_theta	Logical. Whether to use theta in the binomial model.
binomial_joint_alpha	Logical. Whether to use joint alpha in the binomial model.
binomial_tau_lower	Numeric. The lower bound for tau in the binomial model.

Value

NULL. The function prints suggestions to the console based on the model diagnostics.

catalytic documentation built on April 4, 2025, 5:51 a.m.