loo.brmcoda: Efficient approximate leave-one-out cross-validation (LOO)

In florale/multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

Efficient approximate leave-one-out cross-validation (LOO)

Description

Perform approximate leave-one-out cross-validation based on the posterior likelihood using the loo package. For more details see loo.

Usage

## S3 method for class 'brmcoda'
loo(x, ...)

Arguments

x	A brmcoda object.
...	More brmsfit objects or further arguments passed to the underlying post-processing functions. In particular, see prepare_predictions for further supported arguments.

Value

If just one object is provided, an object of class loo. If multiple objects are provided, an object of class loolist.

See Also

loo.brmsfit

florale/multilevelcoda documentation built on April 21, 2024, 9:44 a.m.