hetGP (1.1.1)

Heteroskedastic Gaussian Process Modeling and Design under Replication.

http://cran.r-project.org/web/packages/hetGP

Performs Gaussian process regression with heteroskedastic noise following Binois, M., Gramacy, R., Ludkovski, M. (2016) . The input dependent noise is modeled as another Gaussian process. Replicated observations are encouraged as they yield computational savings. Sequential design procedures based on the integrated mean square prediction error and lookahead heuristics are provided, and notably fast update functions when adding new observations.

Maintainer: Mickael Binois
Author(s): Mickael Binois, Robert B. Gramacy

License: LGPL

Uses: DiceDesign, MASS, Rcpp, lhs, monomvn, knitr

Released over 1 year ago.