kfold-generic: Generic function for K-fold cross-validation for developers

In jgabry/loo: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models

Generic function for K-fold cross-validation for developers

Description

For developers of Bayesian modeling packages, loo includes a generic function kfold() so that methods may be defined for K-fold CV without name conflicts between packages. See, for example, the kfold() methods in the rstanarm and brms packages.

The Value section below describes the objects that kfold() methods should return in order to be compatible with loo_compare() and the loo package print methods.

Usage

kfold(x, ...)

is.kfold(x)

Arguments

x	A fitted model object.
...	Arguments to pass to specific methods.

Value

For developers defining a kfold() method for a class "foo", the kfold.foo() function should return a list with class c("kfold", "loo") with at least the following named elements:

• "estimates": A ⁠1x2⁠ matrix containing the ELPD estimate and its standard error. The matrix must have row name "elpd_kfold" and column names "Estimate" and "SE".

• "pointwise": A Nx1 matrix with column name "elpd_kfold" containing the pointwise contributions for each data point.

It is important for the object to have at least these classes and components so that it is compatible with other functions like loo_compare() and print() methods.

jgabry/loo documentation built on Nov. 26, 2024, 5:29 p.m.