Gaussian Processes Modeling

A computationally stable approach of fitting a Gaussian Process (GP) model to a deterministic simulator.


News

GPfit v1.0-8 (Release date: 2019-02-07)

Changes:

  • Removed reverse dependency from test suite.
  • Reverted export of plot.GP().

GPfit v1.0-6 (Release date: 2019-01-15)

Changes:

  • Refactored GP_fit() for improved calculation speed.
  • Refactored predict.GP() for improved prediction speed.
  • Added scale_norm() as helper to rescale dimensions into 0,1 range.
  • Added fitted.GP() method.
  • Added testthat unit tests.

GPfit v1.0-0 (Release date: 2015-04-01)

Changes:

  • Housekeeping changes only: added inst/CITATION file and NEWS file, including retroactive listing of changes
  • Version number coincides with publication of JSS paper (see references).

GPfit v0.2-1 (Release date: 2014-09-03)

Changes:

  • fixed bug in predict() for the Matern correlation function

GPfit v0.2-0 (Release date: 2014-06-24)

Changes:

  • Matern correlation function added to corr_matrix()
  • In corr_matrix(), Gaussian correlation generalized to power exponential.
  • Power exponential correlation with power=1.95 is now default for corr_matrix() and thus for GP_fit.
  • Iterative approach to selecting the nugget implemented in predict.GP().
  • In GP_fit(), the argument optim_start was added, to allow user-specified initial parameter values for optim(), in addition to those generated automatically.

GPfit v0.1-0 (Release date: 2012-08-09)

  • Initial release

Reference manual

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install.packages("GPfit")

1.0-8 by Hugh Chipman, a month ago


Browse source code at https://github.com/cran/GPfit


Authors: Blake MacDoanld [aut] , Hugh Chipman [aut, cre] , Chris Campbell [ctb] , Pritam Ranjan [aut]


Documentation:   PDF Manual  


GPL-2 license


Imports lhs, lattice

Suggests testthat


Imported by binaryGP, calibrateBinary, phylocurve, rBayesianOptimization.

Suggested by IGP, mlr.


See at CRAN