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/.

Install the latest version of this package by entering the following in R:
AuthorRobin K. S. Hankin
Date of publication2013-12-09 08:22:43
MaintainerRobin K. S. Hankin <>

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Man pages beta1 estimator estimator for beta2 Expectation of beta, given theta, phi and d

blockdiag: Assembles matrices blockwise into a block diagonal matrix

C1: Matrix of distances from D1 to D2

cov.p5.supp: Covariance function for posterior distribution of z Create new toy datasets Function to join to t.vec to give matrix D1 Augments observation points with parameters

dists.2frames: Distance between two points

EK.eqn10.supp: Posterior mean of K

etahat: Expectation of computer output

E.theta.toy: Expectation and variance with respect to theta

extractor.toy: Extracts lat/long matrix and theta matrix from D2.

Ez.eqn7.supp: Expectation of z given y, beta2, phi

Ez.eqn9.supp: Expectation as per equation 10 of KOH2001

h1: Basis functions

H1.toy: Basis functions for D1 and D2 Toy example of hbar (section 4.2) H function

is.positive.definite: Is a matrix positive definite?

MH: Very basic implementation of the Metropolis-Hastings...

p.eqn4.supp: Apostiori probability of psi1

p.eqn8.supp: A postiori probability of hyperparameters Functions to create or change hyperparameters

p.page4: A postiori probability of 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 Integrals needed in KOH2001

V1: Distance matrix

V2: distance between observation points

Vd: Variance matrix for d Variance matrix for observations

W: covariance matrix for beta

W1: Variance matrix for beta1hat

W2: variance matrix for beta2

Functions Man page Man page Man page Man page
blockdiag Man page
C1 Man page
computer.model Man page
Cov.eqn9.supp Man page
cov.p5.supp Man page Man page Man page
D1.toy Man page Man page
D2.toy Man page
dists.2frames Man page
d.toy Man page
Edash.theta.toy Man page
EK.eqn10.supp Man page
etahat Man page
E.theta.toy Man page
extractor.toy Man page
Ez.eqn7.supp Man page
Ez.eqn9.supp Man page
Ez.eqn9.supp.vector Man page
h1.toy Man page
H1.toy Man page
h2.toy Man page
H2.toy Man page Man page Man page Man page Man page Man page
is.positive.definite Man page
MH Man page
model.inadequacy Man page
p.eqn4.supp Man page
p.eqn8.supp Man page
p.eqn8.supp.vector Man page
p.equationn4.supp Man page
phi.change Man page Man page
phi.toy Man page
phi.true Man page
phi.true.toy Man page
p.page4 Man page
prob.psi1 Man page
prob.psi2 Man page
prob.theta Man page
reality Man page
sample.theta Man page
stage1 Man page
stage2 Man page
stage3 Man page
symmetrize Man page
tee Man page Man page
theta.toy Man page
toys Man page Man page
t.vec.toy Man page
V1 Man page
V2 Man page
Vd Man page Man page
V.toy Man page
W Man page
W1 Man page
W2 Man page
X.dist.toy Man page
x.toy Man page
x.toy2 Man page
x.vec Man page
y.toy Man page
z.toy Man page

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