predict.gmjmcmc_parallel: Predict using a gmjmcmc result object from a parallel run.

In FBMS: Flexible Bayesian Model Selection and Model Averaging

Predict using a gmjmcmc result object from a parallel run.

Description

Predict using a gmjmcmc result object from a parallel run.

Usage

## S3 method for class 'gmjmcmc_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
...	Additional arguments to pass to merge_results.

Value

A list containing aggregated predictions and per model predictions.

aggr	Aggregated predictions with mean and quantiles.
preds	A list of lists containing individual predictions per model per population in object.

Examples

result <- gmjmcmc.parallel(
 runs = 1,
 cores = 1,
 x = matrix(rnorm(600), 100),
 y = matrix(rnorm(100), 100),
 P = 2,
 transforms = c("p0", "exp_dbl")
)
preds <- predict(result, matrix(rnorm(600), 100))

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