tsxtreme: Bayesian Modelling of Extremal Dependence in Time Series
Version 0.3.1

Characterisation of the extremal dependence structure of time series, avoiding pre-processing and filtering as done typically with peaks-over-threshold methods. It uses the conditional approach of Heffernan and Tawn (2004) which is very flexible in terms of extremal and asymptotic dependence structures, and Bayesian methods improve efficiency and allow for deriving measures of uncertainty. For example, the extremal index, related to the size of clusters in time, can be estimated and samples from its posterior distribution obtained.

Package details

AuthorThomas Lugrin
Date of publication2017-03-23 13:02:32 UTC
MaintainerThomas Lugrin <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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tsxtreme documentation built on May 30, 2017, 3:32 a.m.