Package: anMC 0.2.5

Dario Azzimonti

anMC: Compute High Dimensional Orthant Probabilities

Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors. Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors.

Authors:Dario Azzimonti [aut, cre, cph]

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NEWS

# Install 'anMC' in R:
install.packages('anMC', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

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Last updated 2 years agofrom:a4f7e6057b. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 14 2025
R-4.5-linux-x86_64NOTEMar 14 2025
R-4.4-linux-x86_64NOTEMar 14 2025

Exports:ANMC_GaussconservativeEstimateget_chronotimeMC_GaussmvrnormArmaProbaMaxProbaMinselectActiveDimsselectQdimstrmvrnorm_rej_cpp

Dependencies:mvtnormRcppRcppArmadillo

Citation

To cite package ‘anMC’ in publications use:

Azzimonti D (2023). anMC: Compute High Dimensional Orthant Probabilities. R package version 0.2.5, https://CRAN.R-project.org/package=anMC.

Corresponding BibTeX entry: 

  @Manual{,
    title = {anMC: Compute High Dimensional Orthant Probabilities},
    author = {Dario Azzimonti},
    year = {2023},
    note = {R package version 0.2.5},
    url = {https://CRAN.R-project.org/package=anMC},
  }

Readme and manuals

anMC

anMC is a R package to efficiently compute orthant probabilities of high-dimensional Gaussian vectors. The method is applied to compute conservative estimates of excursion sets of functions under Gaussian random field priors. This is an upgrade on the previously existent package ConservativeEstimates. See the paper Azzimonti, D. and Ginsbourger D. (2018) for more details.

Features

The package main functions are:

  • ProbaMax: the main function for high dimensional othant probabilities. Computes P(max X > t), where X is a Gaussian vector and t is the selected threshold. The function computes the probability with the decomposition explained here. It implements both the GMC and GANMC algorithms. It allows user-defined functions for the core probability estimate (defaults to pmvnorm of the package mvtnorm) and the truncated normal sampler (defaults to trmvrnorm_rej_cpp) required in the method.

  • ProbaMin: analogous of ProbaMax but used to compute P(min X < t), where X is a Gaussian vector and t is the selected threshold. This function computes the probability with the decomposition explained here. It implements both the GMC and GANMC algorithms.

  • conservativeEstimate : the main function for conservative estimates computation. Requires the mean and covariance of the posterior field at a discretization design.

Installation

To install the latest version of the package run the following code from a R console:

if (!require("devtools"))
  install.packages("devtools")
devtools::install_github("dazzimonti/anMC")
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. Preprint at hal-01289126

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