predict.LSBP_Gibbs: Predict method for the LSBP

In tommasorigon/DLSBP: Tractable Bayesian density regression via logit stick-breaking priors

Predict method for the LSBP

Description

Predict method for a LSBP model estimated using the LSBP_Gibbs function.

Usage

## S3 method for class 'LSBP_Gibbs'
predict(object, type = "mean", newdata = NULL, threshold = NULL, ...)

Arguments

object	An object of class LSBP_Gibbs.
type	String indicating the type of prediction. The available options are type="mean",type="predictive", type="variance", or type="cdf". See "Details".
newdata	A new data frame containing the same variables declared in Formula. If missing, the dataset provided for estimation is used.
threshold	Only needed if type="cdf" is selected. See "Details".
...	Further arguments passed to or from other methods.

Details

The method predict.LSBP_Gibbs produces a sample of predicted values, obtained by evaluating the conditional mean of the LSBP model or the predictive distribution, using the observations contained in the newdata data frame.

If type="mean", then a sample from the posterior of the mean of a LSBP model is returned. If type="predictive" is selected, then a sample from the predictive distribution is returned. If type="variance", then a sample from the posterior distribution of the LSBP variance is returned. If type="cdf", then a sample from the posterior distribution of the LSBP cumulative distribution function is returned, evaluated at threshold.

tommasorigon/DLSBP documentation built on Feb. 28, 2023, 8:50 a.m.