RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events

Dublin Core

Title

RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events

Subject

extreme value analysis, hypothesis of stationarity, non-parametric tests, records,
R

Description

The study of non-stationary behavior in the extremes is important to analyze data
in environmental sciences, climate, finance, or sports. As an alternative to the classical
extreme value theory, this analysis can be based on the study of record-breaking events.
The R package RecordTest provides a useful framework for non-parametric analysis of
non-stationary behavior in the extremes, based on the analysis of records. The underlying
idea of all the non-parametric tools implemented in the package is to use the distribution
of the record occurrence under series of independent and identically distributed continuous
random variables, to analyze if the observed records are compatible with that behavior.
Two families of tests are implemented. The first only requires the record times of the series,
while the second includes more powerful tests that join the information from different types
of records: upper and lower records in the forward and backward series. The package also
offers functions that cover all the steps in this type of analysis such as data preparation,
identification of the records, exploratory analysis, and complementary graphical tools.
The applicability of the package is illustrated with the analysis of the effect of global
warming on the extremes of the daily maximum temperature series in Zaragoza, Spain

Creator

Jorge Castillo-Mateo

Source

https://www.jstatsoft.org/article/view/v106i05

Publisher

University of Zaragoza

Date

March 2023

Contributor

Fajar bagus W

Format

PDF

Language

English

Type

Text

Files

Citation

Jorge Castillo-Mateo, “RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8296.