tsxtreme: Bayesian Modelling of Extremal Dependence in Time Series

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) <DOI:10.1111/j.1467-9868.2004.02050.x> 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
MaintainerThomas Lugrin <thomas.lugrin@alumni.epfl.ch>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the tsxtreme package in your browser

Any scripts or data that you put into this service are public.

tsxtreme documentation built on May 2, 2019, 2:11 a.m.