anMC {anMC}R Documentation

anMC package

Description

Efficient estimation of high dimensional orthant probabilities. The package main functions are:

Details

Package: anMC
Type: Package
Version: 0.2.2
Date: 2019-10-23

Note

This work was supported in part by the Swiss National Science Foundation, grant number 146354 and the Hasler Foundation, grant number 16065.

Author(s)

Dario Azzimonti (dario.azzimonti@gmail.com) . Thanks to David Ginsbourger for the fruitful discussions and his continuous help in testing and improving the package.

References

Azzimonti, D. and Ginsbourger, D. (2018). Estimating orthant probabilities of high dimensional Gaussian vectors with an application to set estimation. Journal of Computational and Graphical Statistics, 27(2), 255-267. DOI: 10.1080/10618600.2017.1360781

Azzimonti, D. (2016). Contributions to Bayesian set estimation relying on random field priors. PhD thesis, University of Bern.

Bolin, D. and Lindgren, F. (2015). Excursion and contour uncertainty regions for latent Gaussian models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 77(1):85–106.

Chevalier, C. (2013). Fast uncertainty reduction strategies relying on Gaussian process models. PhD thesis, University of Bern.

Dickmann, F. and Schweizer, N. (2014). Faster comparison of stopping times by nested conditional Monte Carlo. arXiv preprint arXiv:1402.0243.

Genz, A. (1992). Numerical computation of multivariate normal probabilities. Journal of Computational and Graphical Statistics, 1(2):141–149.

Genz, A. and Bretz, F. (2009). Computation of Multivariate Normal and t Probabilities. Lecture Notes in Statistics 195. Springer-Verlag.

Horrace, W. C. (2005). Some results on the multivariate truncated normal distribution. Journal of Multivariate Analysis, 94(1):209–221.

Robert, C. P. (1995). Simulation of truncated normal variables. Statistics and Computing, 5(2):121–125.


[Package anMC version 0.2.2 Index]