predict_functions: Use the model-estimated covariance parameters from gpdpgrow()...

In growfunctions: Bayesian Non-Parametric Dependent Models for Time-Indexed Functional Data

Use the model-estimated covariance parameters from gpdpgrow() or gmrdpgrow to predict the function at future time points.

Description

This is the generic predict_functions method. See the following functions for the details about different data structures:

Usage

predict_functions(object, J, ...)

Arguments

object	Object of class gpdpgrow orgmrfdpgrow().
J	Scalar denoting number of draws to take from posterior predictive for each unit. Defaults to J = 500.
...	further arguments passed to or from other methods.

Details

• predict_functions.gpdpgrow for objects of class gpdpgrow

• predict_functions.gmrfdpgrow for objects of class gmrfdpgrow

growfunctions documentation built on June 22, 2024, 11:49 a.m.