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    Predictive Models For Time To Acceptance: An Example Using “Hurricane” Articles in AMS Journals

    Source: Bulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 006::page 879
    Author:
    Hodges, Robert E.
    ,
    Elsner, James B.
    ,
    Jagger, Thomas H.
    DOI: 10.1175/BAMS-D-11-00133.1
    Publisher: American Meteorological Society
    Abstract: rs demonstrate a statistical model for the time it takes a manuscript to be accepted for publication. The manuscript received and accepted dates from published manuscripts with the term ?hurricane? in the title are obtained from the American Meteorological Society's online publication search feature. The time to acceptance as the difference in days between these two dates is modeled using a Bayesian approach. Assuming an article picked at random gets published, draws from the posterior distribution of the modeled time-to-acceptance parameter indicate about a 12% chance that it will spend more than 210 days (7 months) in review. The model can be adapted to fit similar data obtained using other search criteria.
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      Predictive Models For Time To Acceptance: An Example Using “Hurricane” Articles in AMS Journals

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4215253
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    • Bulletin of the American Meteorological Society

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    contributor authorHodges, Robert E.
    contributor authorElsner, James B.
    contributor authorJagger, Thomas H.
    date accessioned2017-06-09T16:44:00Z
    date available2017-06-09T16:44:00Z
    date copyright2012/06/01
    date issued2012
    identifier issn0003-0007
    identifier otherams-73169.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4215253
    description abstractrs demonstrate a statistical model for the time it takes a manuscript to be accepted for publication. The manuscript received and accepted dates from published manuscripts with the term ?hurricane? in the title are obtained from the American Meteorological Society's online publication search feature. The time to acceptance as the difference in days between these two dates is modeled using a Bayesian approach. Assuming an article picked at random gets published, draws from the posterior distribution of the modeled time-to-acceptance parameter indicate about a 12% chance that it will spend more than 210 days (7 months) in review. The model can be adapted to fit similar data obtained using other search criteria.
    publisherAmerican Meteorological Society
    titlePredictive Models For Time To Acceptance: An Example Using “Hurricane” Articles in AMS Journals
    typeJournal Paper
    journal volume93
    journal issue6
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-11-00133.1
    journal fristpage879
    journal lastpage882
    treeBulletin of the American Meteorological Society:;2012:;volume( 093 ):;issue: 006
    contenttypeFulltext
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    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