# Code Calibration in a Bayesian Framework

## Documentation for package ‘CaliCo’ version 0.1.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

CaliCo-package | Bayesian calibration for computational codes
%<% | Operator to define active bindings variables
calibrate | Generates 'calibrate.class' objects
calibrate.class | A Reference Class to generates different 'calibrate.class' objects
CaliCo | Bayesian calibration for computational codes
chain | Return the MCMC chain in a 'data.frame'
DefPos | Function that deals with negative eigen values in a matrix not positive definite
estimators | Return Maximum A Posteriori (MAP) and Mean A Posteriori estimation of a calibration
forecast | Generates a forecast base on calibration run with 'calibrate'
forecast.class | A Reference Class to generates differents 'forecast.class' objects
Kernel.class | A Reference Class to generates differents model objects
kernel.fun | Generates covariances matrices thanks to 'Kernel.class'
MetropolisHastingsCpp | C++ implementation of the algorithm for parameter calibration (without discrepancy)
MetropolisHastingsCppD | C++ implementation of the algorithm for parameter calibration (with discrepancy)
model | Generates 'model.class' objects.
model.class | A Reference Class to generates differents model objects
multivariate | Simulate from a Multivariate Normal Distribution
prior | Generates 'prior.class' objects.
prior.class | A Reference Class to generate differents 'prior.class' objects
seqDesign.class | A Reference Class to generate a better Model2 or Model4 'model.class' objects
sequentialDesign | Calibration with a sequential design
unscale | Function which unscale un matrix or a vector
unscale.matrix.diag | Function which unscale only the diagonal component of a matrix
unscale.vector | Function which unscale a vector between two bounds