predict.mjmcmc_parallel: Predict using a mjmcmc result object from a parallel run.

In FBMS: Flexible Bayesian Model Selection and Model Averaging

Predict using a mjmcmc result object from a parallel run.

Description

Predict using a mjmcmc result object from a parallel run.

Usage

## S3 method for class 'mjmcmc_parallel'
predict(
  object,
  x,
  link = function(x) x,
  quantiles = c(0.025, 0.5, 0.975),
  x_train = NULL,
  ...
)

Arguments

object	The model to use.
x	The new data to use for the prediction, a matrix where each row is an observation.
link	The link function to use
quantiles	The quantiles to calculate credible intervals for the posterior modes (in model space).
x_train	Training design matrix to be provided when imputations are to be made from them
...	Not used.

Value

A list containing aggregated predictions.

mean	Mean of aggregated predictions.
quantiles	Quantiles of aggregated predictions.

Examples

result <- mjmcmc.parallel(runs = 1, 
cores = 1, 
x = matrix(rnorm(600), 100),
y = matrix(rnorm(100), 100), 
loglik.pi = gaussian.loglik)
preds <- predict(result, matrix(rnorm(600), 100))

FBMS documentation built on Sept. 13, 2025, 1:09 a.m.