predict.mvrm: Model predictions

In BNSP: Bayesian Non- And Semi-Parametric Model Fitting

Model predictions

Description

Provides predictions and posterior credible/prediction intervals for given feature vectors.

Usage

## S3 method for class 'mvrm'
predict(object, newdata, interval = c("none", "credible", "prediction"), 
                       level = 0.95, ind.preds=FALSE, ...)

Arguments

object	an object of class "mvrm", usually a result of a call to mvrm.
newdata	data frame of feature vectors to obtain predictions for. If newdata is missing, the function will use the feature vectors in the data frame used to fit the mvrm object.
interval	type of interval calculation.
level	the level of the credible interval.
ind.preds	Binary indicator. If set to TRUE the function returns additionally the predictions per individual MCMC sample.
...	other arguments.

Details

The function returns predictions of new responses or the means of the responses for given feature vectors. Predictions for new responses or the means of new responses are the same. However, the two differ in the associated level of uncertainty: response predictions are associated with wider (prediction) intervals than mean response predictions. To obtain prediction intervals (for new responses) the function samples from the normal distributions with means and variances as sampled during the MCMC run.

Value

Predictions for given covariate/feature vectors.

Author(s)

Georgios Papageorgiou [e-mail]

See Also

mvrm

Examples

#see \code{mvrm} example

BNSP documentation built on May 31, 2023, 7:05 p.m.