Package: calibrator 1.2-9

calibrator: Bayesian Calibration of Complex Computer Codes

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/.

Authors:Robin K. S. Hankin [aut, cre]

calibrator_1.2-9.tar.gz
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calibrator.pdf |calibrator.html✨
calibrator/json (API)

# Install 'calibrator' in R:
install.packages('calibrator', repos = c('https://robinhankin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/robinhankin/calibrator/issues

Datasets:

On CRAN:

4.59 score 1 stars 3 packages 43 scripts 805 downloads 58 exports 4 dependencies

Last updated 4 years agofrom:8637464ef2. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:beta1hat.funbeta2hat.funbetahat.fun.kohbetahat.fun.koh.vectorblockdiagC1computer.modelCov.eqn9.suppcov.p5.suppcreate.new.toy.datasetsD1.funD2.fundists.2framesE.theta.toyEdash.theta.toyEK.eqn10.suppetahatextractor.toyEz.eqn7.suppEz.eqn9.suppEz.eqn9.supp.vectorh.funH.funh1.toyH1.toyh2.toyH2.toyhbar.fun.toyhh.funht.funis.positive.definiteMHmodel.inadequacyp.eqn4.suppp.eqn8.suppp.eqn8.supp.vectorp.page4phi.changephi.fun.toyphi.true.toyprob.psi1prob.psi2prob.thetasample.thetastage1stage2stage3symmetrizet.funteett.funV.funV1V2VdWW1W2

Dependencies:cubatureemulatormvtnormRcpp

Calex: a cookbook for the emulator package

Rendered fromcalex.Rnwusingutils::Sweaveon Nov 20 2024.

Last update: 2019-03-06
Started: 2019-03-06

Readme and manuals

Help Manual

Help pageTopics
Bayesian Calibration of Complex Computer Codescalibrator-package calibrator
beta1 estimatorbeta1hat.fun
estimator for beta2beta2hat.fun
Expectation of beta, given theta, phi and dbetahat.fun.koh betahat.fun.koh.vector
Assembles matrices blockwise into a block diagonal matrixblockdiag
Matrix of distances from D1 to D2C1
Covariance function for posterior distribution of zCov.eqn9.supp cov.p5.supp
Create new toy datasetscreate.new.toy.datasets
Function to join x.star to t.vec to give matrix D1D1.fun
Augments observation points with parametersD2.fun
Distance between two pointsdists.2frames
Expectation and variance with respect to thetaE.theta.toy Edash.theta.toy
Posterior mean of KEK.eqn10.supp
Expectation of computer outputetahat
Extracts lat/long matrix and theta matrix from D2.extractor.toy
Expectation of z given y, beta2, phiEz.eqn7.supp
Expectation as per equation 10 of KOH2001Ez.eqn9.supp Ez.eqn9.supp.vector
H functionH.fun
Basis functionsh1.toy h2.toy
Basis functions for D1 and D2H1.toy H2.toy
Toy example of hbar (section 4.2)hbar.fun.toy
Is a matrix positive definite?is.positive.definite
Very basic implementation of the Metropolis-Hastings algorithmMH
Apostiori probability of psi1p.eqn4.supp p.equationn4.supp
A postiori probability of hyperparametersp.eqn8.supp p.eqn8.supp.vector
A postiori probability of hyperparametersp.page4
Functions to create or change hyperparametersphi.change phi.fun.toy
A priori probability of psi1, psi2, and thetaprob.psi1 prob.psi2 prob.theta sample.theta
Realitycomputer.model model.inadequacy phi.true phi.true.toy reality
Stage 1,2 and 3 optimization on toy datasetstage1 stage2 stage3
Symmetrize an upper triangular matrixsymmetrize
Auxiliary functions for equation 9 of the supplementh.fun tee
Toy datasetsd.toy D1.toy D2.toy phi.toy t.vec.toy theta.toy toys V.toy X.dist.toy x.toy x.toy2 x.vec y.toy z.toy
Integrals needed in KOH2001hh.fun ht.fun t.fun tt.fun
Variance matrix for observationsV.fun
Distance matrixV1
distance between observation pointsV2
Variance matrix for dVd
covariance matrix for betaW
Variance matrix for beta1hatW1
variance matrix for beta2W2