Constarium
← Search

Data · dataset · 2026

Bootstrap methods for statistical inference. Part II: Extreme-value analysis

Listed in National Center for Atmospheric Research

This paper is the sequel to a companion paper on bootstrap resampling that reviews bootstrap methodology for making statistical inferences for atmospheric science applications where the necessary assumptions are often not met for the most commonly used resampling procedures.

Description

In particular, this sequel addresses extreme-value analysis applications with discussion on the challenges for finding accurate bootstrap methods in this context.

New bootstrap code from the R packages "distillery" and "extRemes" is introduced. It is further found that one approach for accurate confidence intervals in this setting is not well suited to the case when the random sample's distribution is not stationary.

Links

Get the data

Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Researche6b6abaa-dd1a-47ce-9860-84bd4b107ca510 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:370901enrichment · data ucar edutaxonomy-embedding@1.1.0title+keywords+description (77%)
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0