CaliCo: Bayesian calibration for computational codes

In CaliCo: Code Calibration in a Bayesian Framework

Description

The CaliCo package provides five main functions: model, prior, calibrate, forecast and sequentialDesign.

Details

Package: CaliCo

Type: Package

Version: 0.1.1

Date: 2018-04-13

License: GPL-2 | GPL-3

Author(s)

Mathieu Carmassi

Maintainer: [e-mail]

References

Bachoc, F., Blois, G., Garnier, J., and Martinez, J.-M. (2014). Calibration and improved prediction of computer models by universal kriging. Computational Statistics and Data Analysis, pages 81–97

Bayarri, M., Berger, J., Sacks, P. R., Cafeo, J. A., Cavendish, J., Lin, C. H., and Tu, J. (2007 b). A framework for validation of computer models. Technometrics.

Carmassi, M., Barbillon ,P., Chiodetti, M., Keller, M., Parent, E. (2018). Bayesian calibration of a numerical code for prediction, arXiv preprint arXiv:1801.01810.

Cox, D., Park, J. S., and Singer, C. (2001). A statistical method for tuning a computer code to a data base. Computational Statistics and Data Analysis.

Damblin, G. (2015). Contributions statistiques au calage et à la validation des codes de calculs. PhD thesis, University Paris-Saclay

Hastings, W. K. (1970). Mont carlo sampling methods using markov chains and their applications. Biometrika.

Higdon, D., Kennedy, M. C., Cavendish, J., Cafeo, J., and Ryne, R. (2004). Combining field data and computer simulations for calibration and prediction. SIAM Journal on Scientific Computing.

Kennedy, M. C. and O’Hagan, A. (2001). Bayesian calibration of computer models. Journal of the Royal Statistical Society, serie B, Methodological.

Kennedy, M. C. and O’Hagan, A. (2001b). Supplementary details on bayesian calibration of computer models. Journal of the Royal Statistical Society, serie B, Methodological.

Liu, F., Bayarri, S., and Berger, J. (2009). Modularization in bayesian analysis, with emphasis on analysis of computer models. Bayesian Analysis, pages 119–150.

Robert, C. (1996). Méthodes de monte carlo par chaines de markov. economica.

Roustant, O., Ginsbourger, D., and Devills, Y. (2012). Dicekriging, diceoptim : Two r packages for the analysis of computer experiments by kriging-based metamodeling and optimization. Journal of Statistical Software.

Sacks, J., Welch, W. J., and Toby J. Mitchell, H. P. W. (1989). Design and analysis of computer experiments. Statistical science, pages 409–423.

Santner, T., Williams, B., and Notz, W. (2003). The Design and Analysis of Computer Experiments. Springer-Verlab.

Examples

# Introduction to CaliCo
## Not run: vignette("CaliCo-introduction")

CaliCo documentation built on May 2, 2019, 4:05 p.m.