YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of Atmospheric and Oceanic Technology
    • View Item
    •   YE&T Library
    • AMS
    • Journal of Atmospheric and Oceanic Technology
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

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

    Source: Journal of Atmospheric and Oceanic Technology:;2020:;volume( ):;issue: -::page 1
    Author:
    Gilleland, Eric
    DOI: 10.1175/JTECH-D-20-0070.1
    Publisher: American Meteorological Society
    Abstract: 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. 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.
    • Download: (858.8Kb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

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

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4264599
    Collections
    • Journal of Atmospheric and Oceanic Technology

    Show full item record

    contributor authorGilleland, Eric
    date accessioned2022-01-30T18:10:03Z
    date available2022-01-30T18:10:03Z
    date copyright9/29/2020 12:00:00 AM
    date issued2020
    identifier issn0739-0572
    identifier otherjtechd200070.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264599
    description abstractThis 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. 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.
    publisherAmerican Meteorological Society
    titleBootstrap methods for statistical inference. Part II: Extreme-value analysis
    typeJournal Paper
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-20-0070.1
    journal fristpage1
    journal lastpage36
    treeJournal of Atmospheric and Oceanic Technology:;2020:;volume( ):;issue: -
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian