predict_functions

Object of class <code>gpdpgrow</code> or<code>gmrfdpgrow()</code>.

object

Scalar denoting number of draws to take from posterior predictive for each unit.
Defaults to <code>J = 500</code>.

further arguments passed to or from other methods.


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


manip

Estimates a collection of time-indexed functions under
either of Gaussian process (GP) or intrinsic Gaussian Markov
random field (iGMRF) prior formulations where a Dirichlet process
mixture allows sub-groupings of the functions to share the same
covariance or precision parameters.  The GP and iGMRF formulations
both support any number of additive covariance or precision terms,
respectively, expressing either or both of multiple trend and
seasonality.

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

Description

Usage

Arguments

Details