obpred

output from <code><a rd-options="" href="/link/obfit?package=outerbase&version=0.1.0" data-mini-rdoc="outerbase::obfit">obfit</a></code>

obmodel

a new m by d sized matrix of inputs

This function allows for turning an <code>obmodel</code> into predictions with 
mean and variance.

High-dimensional regression using outer product models. Research on the methods is currently under investigation and published resources will be posted as they are available. As the method is new, the website is the best resource for understanding the principals. Some of the core ideas are based on Plumlee and coauthors' work on analysis of grid-structured experiments described in Plumlee (2014) <doi:10.1080/01621459.2014.900250> and Plumlee, Erickson, Ankenman, Lawrence (2021) <doi:10.1093/biomet/asaa084>. Some additional textbooks for additional information on Gaussian processes are Rasmussen and Williams (2005) <doi:10.7551/mitpress/3206.001.0001> and Gramacy (2022) <doi:10.1201/9780367815493>.

Matthew Plumlee

outerbase

Outer Product Regression

obpred function

output from <code><a rd-options='' href='obfit'>obfit</a></code>

obpred: Prediction from outerbase

Description

Usage

Arguments

Value

See Also