Software

An R-Package that implements an sequential method to compute p-values for Monte Carlo tests. The algorithm is particularly useful for bootstrap or permutation tests. It now includes extensions to multiple testing.

The package is available on CRAN.

This package calibrates thresholds of control charts such as CUSUM charts based on past data, taking estimation error into account.

This package is available on CRAN. Current development versions are available on bitbucket. An article describing the package is available in the R-journal.

A toolbox for systemic risk based on liabilities matrices. Contains a Gibbs sampler for liabilities matrices where only row and column sums of the liabilities matrix are observed. It is based on the following paper:
Gandy, Axel and Veraart, Luitgard A. M., A Bayesian Methodology for Systemic Risk Assessment in Financial Networks (March 19, 2015). To appear in Management Science. Available at SSRN http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2580869 This package is available on CRAN. It contains a short example.

An implementation of the chopthin-algorithm for resampling of particles described in
G&Lau (2015). The chopthin algorithm for resampling. arXiv:1502.07532
The implementation is C++ based (chopthin_C++.zip contains the main code and an example). Also available are an R-package (chopthin on CRAN) a python package and a MATLAB MEX file (chopthin_MEX.zip).

These functions implement the method described in the Appendix of Gandy, Kvaloy, Bottle & Zhou (2010), Biometrika 97 (2): 375-388. The implementation is written in R.

It is available in a git repository on Bitbucket

This package provides efficient MCMC algorithms for uniform sampling of graphs conditional on vertex level data. It is based on the following paper:
J. Scott and A. Gandy. State-dependent kernel selection for conditional sampling of graphs. Journal of Computational and Graphical Statistics, 2019. Accepted for publication. arXiv:1809.06758 [stat.ME]. This package is available on GitHub.

This package provides unit tests for MCMC and Monte Carlo methods. It is based on the following paper:
A. Gandy and J. Scott. Unit Testing for MCMC and other Mone Carlo Meethods, 2020. arXiv:2001.06465 [stat.ME]. This package is available on CRAN and on bitbucket.