graphicalExtremes v0.1.0
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Statistical Methodology for Graphical Extreme Value Models
Statistical methodology for sparse multivariate extreme value models. Methods are
provided for exact simulation and statistical inference for multivariate Pareto distributions
on graphical structures as described in the paper 'Graphical Models for Extremes' by
Engelke and Hitz (2018) <arXiv:1812.01734>.
Readme
graphicalExtremes
The goal of graphicalExtremes is to provide an implementation of the statistical methodology paper Engelke and Hitz (2019, JRSSB) for sparse multivariate extreme value models. This includes exact simulation algorithms and statistical inference methods for multivariate Pareto distributions on graphical structures.
Installation
You can install the development version of graphicalExtremes from GitHub with:
# install.packages("devtools")
devtools::install_github("sebastian-engelke/graphicalExtremes")
Functions in graphicalExtremes
| Name | Description | |
| emp_chi | Empirical estimation of extremal correlation \(\chi\) | |
| rmpareto | Sampling of a multivariate Pareto distribution | |
| rmpareto_tree | Sampling of a multivariate Pareto distribution on a tree | |
| emp_chi_mat | Empirical estimation of extremal correlation matrix \(\chi\) | |
| dim_Gamma | Is Gamma square matrix? | |
| Gamma2chi | Transformation of the Huesler--Reiss variogram \(\Gamma\) to extremal correlation \(\chi\) | |
| simu_px_dirichlet | Simulate Dirichlet extremal functions | |
| simu_px_HR | Simulate HR extremal functions | |
| data2mpareto | Data standardization to multivariate Pareto scale | |
| Gamma2Sigma | Transformation of \(\Gamma\) matrix to \(\Sigma^{(k)}\) matrix | |
| mst_HR | Fitting of Huesler--Reiss minimum spanning tree | |
| Gamma2chi_3D | Compute theoretical \(\chi\) in 3D | |
| simu_px_tree_HR | Simulate HR extremal functions on a tree | |
| complete_Gamma | Completion of Gamma matrix on block graphs | |
| chi2Gamma | Transformation of extremal correlation \(\chi\) to the Huesler--Reiss variogram \(\Gamma\) | |
| fmpareto_HR | Parameter fitting for multivariate Huesler--Reiss Pareto distribution | |
| Gamma2graph | Transformation of \(\Gamma\) matrix to graph object | |
| select_edges | Select edges to add to a graph | |
| emp_vario | Estimation of the variogram matrix \(\Gamma\) of the Huesler--Reiss distribution | |
| simu_px_tree_dirichlet | Simulate Dirichlet extremal functions on a tree | |
| logLH_HR | Full censored log-likelihood of HR model | |
| Sigma2Gamma | Transformation of \(\Sigma^{(k)}\) matrix to \(\Gamma\) matrix | |
| mparetomargins | Marginalize multivariate Pareto dataset | |
| set_graph_parameters | Set graphical parameters | |
| par2Gamma | Create \(\Gamma\) from vector | |
| fmpareto_graph_HR | Parameter fitting for multivariate Huesler--Reiss Pareto distributions on block graphs | |
| graphicalExtremes | graphicalExtremes: Statistical methodology for graphical extreme value models. | |
| logdV_HR | Compute the exponent measure density of HR distribution | |
| logdVK_HR | Compute censored exponent measure | |
| rmstable | Sampling of a multivariate max-stable distribution | |
| simu_px_tree_logistic | Simulate logistic extremal functions on a tree | |
| rmstable_tree | Sampling of a multivariate max-stable distribution on a tree | |
| simu_px_logistic | Simulate logistic extremal functions | |
| simu_px_neglogistic | Simulate negative logistic extremal functions | |
| unif | Uniform margin | |
| censor | Censor dataset | |
| V_HR | Compute exponent measure | |
| Gamma2par | Extract upper triangular part of \(\Gamma\) | |
| No Results! | ||
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Details
| License | GPL-3 |
| Encoding | UTF-8 |
| LazyData | true |
| RoxygenNote | 6.1.1 |
| RdMacros | Rdpack |
| NeedsCompilation | no |
| Packaged | 2019-11-06 18:03:38 UTC; engelkes |
| Repository | CRAN |
| Date/Publication | 2019-11-08 09:40:02 UTC |
| imports | grDevices (>= 3.6.0) , igraph (>= 1.2.4.1) , matrixcalc (>= 1.0.3) , mvtnorm (>= 1.0.10) , Rdpack , stats (>= 3.6.0) |
| depends | R (>= 3.6.0) |
| suggests | testthat (>= 2.1.0) |
| Contributors | Adrien S. Hitz, Nicola Gnecco |
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