R/loo_moment_matching.R
loo_moment_match.Rd
Moment matching algorithm for updating a loo object when Pareto k estimates are large.
loo_moment_match(x, ...) # S3 method for default loo_moment_match( x, loo, post_draws, log_lik_i, unconstrain_pars, log_prob_upars, log_lik_i_upars, max_iters = 30L, k_threshold = 0.7, split = TRUE, cov = TRUE, cores = getOption("mc.cores", 1), ... )
x  A fitted model object. 

...  Further arguments passed to the custom functions documented above. 
loo  A loo object to be modified. 
post_draws  A function the takes 
log_lik_i  A function that takes 
unconstrain_pars  A function that takes arguments 
log_prob_upars  A function that takes arguments 
log_lik_i_upars  A function that takes arguments 
max_iters  Maximum number of moment matching iterations. Usually this
does not need to be modified. If the maximum number of iterations is
reached, there will be a warning, and increasing 
k_threshold  Threshold value for Pareto k values above which the moment matching algorithm is used. The default value is 0.5. 
split  Logical; Indicate whether to do the split transformation or not at the end of moment matching for each LOO fold. 
cov  Logical; Indicate whether to match the covariance matrix of the
samples or not. If 
cores  The number of cores to use for parallelization. This defaults to
the option

The loo_moment_match()
methods return an updated loo
object. The
structure of the updated loo
object is similar, but the method also
stores the original Pareto k diagnostic values in the diagnostics field.
The loo_moment_match()
function is an S3 generic and we provide a
default method that takes as arguments userspecified functions
post_draws
, log_lik_i
, unconstrain_pars
, log_prob_upars
, and
log_lik_i_upars
. All of these functions should take ...
. as an argument
in addition to those specified for each function.
default
: A default method that takes as arguments a
userspecified model object x
, a loo
object and userspecified
functions post_draws
, log_lik_i
, unconstrain_pars
, log_prob_upars
,
and log_lik_i_upars
.
Paananen, T., Piironen, J., Buerkner, P.C., Vehtari, A. (2020). Implicitly Adaptive Importance Sampling. preprint arXiv:1906.08850
# See the vignette for loo_moment_match()