Summary Method for Hierarchical Models

Computes model diagnostics including acceptance rates, posterior mean betas, BART variable importance, and Bayesian R².

Usage

# S3 method for class 'rhierMnlRwMixture'
summary(object, Z = NULL, burn = 0, coefs = NULL, r_verbose = FALSE, ...)

# S3 method for class 'rhierLinearMixture'
summary(object, Z = NULL, burn = 0, coefs = NULL, r_verbose = FALSE, ...)

# S3 method for class 'rhierNegbinRw'
summary(object, Z = NULL, burn = 0, coefs = NULL, r_verbose = FALSE, ...)

Arguments

object

A fitted hierarchical model object.

Z

Optional matrix of unit-level characteristics for R² computation. If NULL and cached DeltaZ draws exist, in-sample R² is still computed.

burn

Number of initial draws to discard (thinned units).

coefs

Integer vector of coefficient indices for R². Default: all.

r_verbose

Print progress? Default FALSE.

...

Ignored.

Value

An object of class summary.rhierModel with print method.