calibrator-package {calibrator} | R Documentation |
Performs Bayesian calibration of computer models as per Kennedy and O'Hagan 2001. The package includes routines to find the hyperparameters and parameters; see the help page for stage1() for a worked example using the toy dataset. A tutorial is provided in the calex.Rnw vignette; and a suite of especially simple one dimensional examples appears in inst/doc/one.dim/.
The DESCRIPTION file:
Package: | calibrator |
Type: | Package |
Title: | Bayesian Calibration of Complex Computer Codes |
Version: | 1.2-8 |
Authors@R: | person(given=c("Robin", "K. S."), family="Hankin", role = c("aut","cre"), email="hankin.robin@gmail.com", comment = c(ORCID = "0000-0001-5982-0415")) |
Depends: | R (>= 2.0.0), emulator (>= 1.2-11), mvtnorm |
Imports: | cubature |
Maintainer: | Robin K. S. Hankin <hankin.robin@gmail.com> |
Description: | Performs Bayesian calibration of computer models as per Kennedy and O'Hagan 2001. The package includes routines to find the hyperparameters and parameters; see the help page for stage1() for a worked example using the toy dataset. A tutorial is provided in the calex.Rnw vignette; and a suite of especially simple one dimensional examples appears in inst/doc/one.dim/. |
License: | GPL-2 |
URL: | https://github.com/RobinHankin/calibrator.git |
BugReports: | https://github.com/RobinHankin/calibrator/issues |
Author: | Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>) |
Index of help topics:
C1 Matrix of distances from D1 to D2 D1.fun Function to join x.star to t.vec to give matrix D1 D2.fun Augments observation points with parameters E.theta.toy Expectation and variance with respect to theta EK.eqn10.supp Posterior mean of K Ez.eqn7.supp Expectation of z given y, beta2, phi Ez.eqn9.supp Expectation as per equation 10 of KOH2001 H.fun H function H1.toy Basis functions for D1 and D2 MH Very basic implementation of the Metropolis-Hastings algorithm V.fun Variance matrix for observations V1 Distance matrix V2 distance between observation points Vd Variance matrix for d W covariance matrix for beta W1 Variance matrix for beta1hat W2 variance matrix for beta2 beta1hat.fun beta1 estimator beta2hat.fun estimator for beta2 betahat.fun.koh Expectation of beta, given theta, phi and d blockdiag Assembles matrices blockwise into a block diagonal matrix calibrator-package Bayesian Calibration of Complex Computer Codes cov.p5.supp Covariance function for posterior distribution of z create.new.toy.datasets Create new toy datasets dists.2frames Distance between two points etahat Expectation of computer output extractor.toy Extracts lat/long matrix and theta matrix from D2. h1.toy Basis functions hbar.fun.toy Toy example of hbar (section 4.2) is.positive.definite Is a matrix positive definite? p.eqn4.supp Apostiori probability of psi1 p.eqn8.supp A postiori probability of hyperparameters p.page4 A postiori probability of hyperparameters phi.fun.toy Functions to create or change hyperparameters prob.psi1 A priori probability of psi1, psi2, and theta reality Reality stage1 Stage 1,2 and 3 optimization on toy dataset symmetrize Symmetrize an upper triangular matrix tee Auxiliary functions for equation 9 of the supplement toys Toy datasets tt.fun Integrals needed in KOH2001
Further information is available in the following vignettes:
calex | Calex: a cookbook for the emulator package (source) |
NA
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
M. C. Kennedy and A. O'Hagan 2001. “Bayesian calibration of computer models”. Journal of the Royal Statistical Society, Series B, 63(3): 425–464
R. K. S. Hankin 2005. “Introducing BACCO, an R bundle for Bayesian analysis of computer code output”, Journal of Statistical Software, 14(16)