hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R
Dublin Core
Title
hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R
Subject
input-dependent noise, level-set estimation, optimization, replication, stochastic
kriging
kriging
Description
An increasing number of time-consuming simulators exhibit a complex noise structure
that depends on the inputs. For conducting studies with limited budgets of evaluations,
new surrogate methods are required in order to simultaneously model the mean and
variance fields. To this end, we present the hetGP package, implementing many recent
advances in Gaussian process modeling with input-dependent noise. First, we describe a
simple, yet efficient, joint modeling framework that relies on replication for both speed
and accuracy. Then we tackle the issue of data acquisition leveraging replication and
exploration in a sequential manner for various goals, such as for obtaining a globally
accurate model, for optimization, or for contour finding. Reproducible illustrations are
provided throughout.
that depends on the inputs. For conducting studies with limited budgets of evaluations,
new surrogate methods are required in order to simultaneously model the mean and
variance fields. To this end, we present the hetGP package, implementing many recent
advances in Gaussian process modeling with input-dependent noise. First, we describe a
simple, yet efficient, joint modeling framework that relies on replication for both speed
and accuracy. Then we tackle the issue of data acquisition leveraging replication and
exploration in a sequential manner for various goals, such as for obtaining a globally
accurate model, for optimization, or for contour finding. Reproducible illustrations are
provided throughout.
Creator
Mickaël Binois
Source
https://www.jstatsoft.org/article/view/v098i13
Publisher
Argonne National Laboratory
Date
May 2021
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Mickaël Binois, “hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R,” Repository Horizon University Indonesia, accessed February 5, 2025, https://repository.horizon.ac.id/items/show/8199.