print_dims

print_dims.psis

print_dims.psis_loo

print_dims.waic

print_dims.kfold

The object returned by <code><a rd-options="" href="/link/psis?package=loo&version=2.1.0" data-mini-rdoc="loo::psis">psis</a></code>, <code><a rd-options="" href="/link/loo?package=loo&version=2.1.0" data-mini-rdoc="loo::loo">loo</a></code>, or
<code><a rd-options="" href="/link/waic?package=loo&version=2.1.0" data-mini-rdoc="loo::waic">waic</a></code>.

Print dimensions of log-likelihood or log-weights matrix

internal

Efficient approximate leave-one-out cross-validation (LOO)
for Bayesian models fit using Markov chain Monte Carlo. The approximation
uses Pareto smoothed importance sampling (PSIS), a new procedure for
regularizing importance weights. As a byproduct of the calculations, we also
obtain approximate standard errors for estimated predictive errors and for
the comparison of predictive errors between models. The package also
provides methods for using stacking and other model weighting techniques
to average Bayesian predictive distributions.

Jonah Gabry

Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian
Models

Aki Vehtari

Andrew Gelman

Yuling Yao

Paul-Christian B<c3><bc>rkner

Ben Goodrich

Juho Piironen

Mans Magnusson

print_dims function

The object returned by <code><a rd-options='' href='psis'>psis</a></code>, <code><a rd-options='' href='loo'>loo</a></code>, or
<code><a rd-options='' href='waic'>waic</a></code>.

Print dimensions of log-likelihood or log-weights matrix — print_dims

Print dimensions of log-likelihood or log-weights matrix

print_dims: Print dimensions of log-likelihood or log-weights matrix

Description

Usage

Arguments