loo_predict.stanreg: Compute weighted expectations using LOO

In csetraynor/aeim: What the Package Does (One Line, Title Case)

Description

These functions are wrappers around the E_loo function (loo package) that provide compatibility for rstanarm models.

Usage

## S3 method for class 'stanreg'
loo_predict(object, type = c("mean", "var",
  "quantile"), probs = 0.5, ..., psis_object = NULL)

## S3 method for class 'stanreg'
loo_linpred(object, type = c("mean", "var",
  "quantile"), probs = 0.5, transform = FALSE, ...,
  psis_object = NULL)

## S3 method for class 'stanreg'
loo_predictive_interval(object, prob = 0.9, ...,
  psis_object = NULL)

Arguments

type	The type of expectation to compute. The options are "mean", "variance", and "quantile".
probs	For computing quantiles, a vector of probabilities.
...	Currently unused.
psis_object	An object returned by psis. If missing then psis will be run internally, which may be time consuming for models fit to very large datasets.
transform	Passed to posterior_linpred.
prob	For loo_predictive_interval, a scalar in (0,1) indicating the desired probability mass to include in the intervals. The default is prob=0.9 (90% intervals).

Value

A list with elements value and pareto_k.

For loo_predict and loo_linpred the value component is a vector with one element per observation.

For loo_predictive_interval the value component is a matrix with one row per observation and two columns (like predictive_interval). loo_predictive_interval(..., prob = p) is equivalent to loo_predict(..., type = "quantile", probs = c(a, 1-a)) with a = (1 - p)/2, except it transposes the result and adds informative column names.

See E_loo and pareto-k-diagnostic for details on the pareto_k diagnostic.

Examples

## Not run: 
if (!exists("example_model")) example(example_model)

# optionally, log-weights can be pre-computed and reused
psis_result <- loo::psis(log_ratios = -log_lik(example_model))

loo_probs <- loo_linpred(example_model, type = "mean", transform = TRUE, psis_object = psis_result)
str(loo_probs)

loo_pred_var <- loo_predict(example_model, type = "var", psis_object = psis_result)
str(loo_pred_var)

loo_pred_ints <- loo_predictive_interval(example_model, prob = 0.8, psis_object = psis_result)
str(loo_pred_ints)

## End(Not run)

csetraynor/aeim documentation built on May 15, 2019, 6:25 p.m.