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    A Degeneracy in Cross-Validated Skill in Regression-based Forecasts

    Source: Journal of Climate:;1993:;volume( 006 ):;issue: 005::page 963
    Author:
    Barnston, Anthony G.
    ,
    van den Dool, Huug M.
    DOI: 10.1175/1520-0442(1993)006<0963:ADICVS>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Highly negative skill scores may occur in regression-based experimental forecast trials in which the data being forecast are withheld in turn from a fixed sample, and the remaining data are used to develop regression relationships-that is, exhaustive cross-validation methods. A small negative bias in skill is amplified when forecasts are verified using the correlation between forecasts and actual data. The same outcome occurs when forecasts are amplitude-inflated in conversion to a categorical system and scored in a ?number of hits? framework. The effect becomes severe when predictor-predictand relationships are weak, as is often the case in climate prediction. Some basic characteristics of this degeneracy are explored for regression-based cross-validation. Simulations using both randomized and designed datasets indicate that the correlation skill score degeneracy becomes important when nearly all of the available sample is used to develop forecast equations for the remaining (very few) points, and when the predictability in the full dependent sample falls short of the conventional requirement for statistical significance for the sample size. The undesirable effects can be reduced with one of the following methodological adjustments: 1) excluding more than a very small portion of the sample from the development group for each cross-validation forecast trial or 2) redefining the ?total available sample? within one cross-validation exercise. A more complete elimination of the effects is achieved by 1) downward adjusting the magnitude of negative correlation skills in proportion to forecast amplitude, 2) regarding negative correlation skills as zero, or 3) using a forecast verification measure other than correlation such as root-mean-square error. When the correlation skill score degeneracy is acknowledged and treated appropriately, cross-validation remains an effective and valid technique for estimating predictive skill for independent data.
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      A Degeneracy in Cross-Validated Skill in Regression-based Forecasts

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4178668
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    contributor authorBarnston, Anthony G.
    contributor authorvan den Dool, Huug M.
    date accessioned2017-06-09T15:18:54Z
    date available2017-06-09T15:18:54Z
    date copyright1993/05/01
    date issued1993
    identifier issn0894-8755
    identifier otherams-4024.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4178668
    description abstractHighly negative skill scores may occur in regression-based experimental forecast trials in which the data being forecast are withheld in turn from a fixed sample, and the remaining data are used to develop regression relationships-that is, exhaustive cross-validation methods. A small negative bias in skill is amplified when forecasts are verified using the correlation between forecasts and actual data. The same outcome occurs when forecasts are amplitude-inflated in conversion to a categorical system and scored in a ?number of hits? framework. The effect becomes severe when predictor-predictand relationships are weak, as is often the case in climate prediction. Some basic characteristics of this degeneracy are explored for regression-based cross-validation. Simulations using both randomized and designed datasets indicate that the correlation skill score degeneracy becomes important when nearly all of the available sample is used to develop forecast equations for the remaining (very few) points, and when the predictability in the full dependent sample falls short of the conventional requirement for statistical significance for the sample size. The undesirable effects can be reduced with one of the following methodological adjustments: 1) excluding more than a very small portion of the sample from the development group for each cross-validation forecast trial or 2) redefining the ?total available sample? within one cross-validation exercise. A more complete elimination of the effects is achieved by 1) downward adjusting the magnitude of negative correlation skills in proportion to forecast amplitude, 2) regarding negative correlation skills as zero, or 3) using a forecast verification measure other than correlation such as root-mean-square error. When the correlation skill score degeneracy is acknowledged and treated appropriately, cross-validation remains an effective and valid technique for estimating predictive skill for independent data.
    publisherAmerican Meteorological Society
    titleA Degeneracy in Cross-Validated Skill in Regression-based Forecasts
    typeJournal Paper
    journal volume6
    journal issue5
    journal titleJournal of Climate
    identifier doi10.1175/1520-0442(1993)006<0963:ADICVS>2.0.CO;2
    journal fristpage963
    journal lastpage977
    treeJournal of Climate:;1993:;volume( 006 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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