loo_conformal {conformalbayes}

Enable leave-one-out conformal predictive intervals for a fit model

Description

Prepares for jackknife(+) conformal prediction by performing Pareto-smoothed importance sampling to yield leave-one-out residuals.

Usage

loo_conformal(fit, ...)

## Default S3 method:
loo_conformal(fit, truth, chain = NULL, est_fun = c("mean", "median"), ...)

## S3 method for class 'stanreg'
loo_conformal(fit, est_fun = c("mean", "median"), ...)

## S3 method for class 'brmsfit'
loo_conformal(fit, est_fun = c("mean", "median"), ...)

Arguments

fit

Model fit; an object with posterior_predict() and log_lik() methods. Can also be an array of posterior predictions.

...

Ignored.

truth

True values to predict. Not required for rstanarm or brms models.

chain

An integer vector identifying the chain numbers for the posterior draws. Should be provided if multiple chains are used.

est_fun

Whether to use the posterior mean (the default) or median as a point estimate.

Value

A modified fit object with an additional class conformal. Calling predictive_interval() on this new object will yield conformal intervals.

References

Vehtari, A., Simpson, D., Gelman, A., Yao, Y., & Gabry, J. (2015). Pareto smoothed importance sampling. arXiv preprint arXiv:1507.02646.

Examples

if (requireNamespace("rstanarm", quietly=TRUE)) suppressWarnings({
    library(rstanarm)
    # fit a simple linear regression
    m = stan_glm(mpg ~ disp + cyl, data=mtcars,
        chains=1, iter=1000,
        control=list(adapt_delta=0.999), refresh=0)

    loo_conformal(m)
})