loo_weights.brma: Extract Normalized PSIS Weights from brma Object

In RoBMA: Robust Bayesian Meta-Analyses

Extract Normalized PSIS Weights from brma Object

Description

Extract the normalized Pareto smoothed importance sampling (PSIS) weights from a brma model object.

Usage

## S3 method for class 'brma'
loo_weights(object, unit = "estimate", ...)

Arguments

object	a brma model object.
unit	output/deletion unit. See add_loo.
...	currently unused.

Details

LOO must first be computed with object <- add_loo(object, unit = unit). This method extracts the stored PSIS object and does not compute LOO.

Value

An S x K matrix for estimate-unit LOO, or S x G matrix for cluster-unit LOO, with posterior samples in rows and LOO targets in columns. Columns are normalized to sum to one.

RoBMA documentation built on May 7, 2026, 5:08 p.m.