Communications for Statistical Applications and Methods

  • 제13권2호
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  • Pages.369-378
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  • 2006
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  • 2287-7843(pISSN)
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  • 2383-4757(eISSN)
한국통계학회 (The Korean Statistical Society)
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Binary Forecast of Heavy Snow Using Statistical Models

  • Sohn, Keon-Tae (Department of Statistics, Pusan National University)
  • 발행 : 2006.08.31
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초록

This Study focuses on the binary forecast of occurrence of heavy snow in Honam area based on the MOS(model output statistic) method. For our study daily amount of snow cover at 17 stations during the cold season (November to March) in 2001 to 2005 and Corresponding 45 RDAPS outputs are used. Logistic regression model and neural networks are applied to predict the probability of occurrence of Heavy snow. Based on the distribution of estimated probabilities, optimal thresholds are determined via true shill score. According to the results of comparison the logistic regression model is recommended.

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참고문헌

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피인용 문헌

  1. Guidance on the choice of threshold for binary forecast modeling vol.25, pp.1, 2008, https://doi.org/10.1007/s00376-008-0083-8