• DocumentCode
    1999409
  • Title

    Prediction method of the transformed data

  • Author

    Sheng, Yao ; Zheng, Xiaogu ; Wu, Guocan ; Li, Yong

  • Author_Institution
    Sch. of Math. Sci., Beijing Normal Univ., Beijing, China
  • fYear
    2011
  • fDate
    16-18 Sept. 2011
  • Firstpage
    5365
  • Lastpage
    5367
  • Abstract
    In Meteorology, we often get data products we need by doing statistical analysis to observation data. It´s very important for meteorology forecasting and disaster warning. When we do statistic modeling, the data are not always normal distribution, so we transform the data to a new one first and then modeling. In this paper, we mainly consider how to forecast origin variable from experience model forecast value. On this question, people always consider less about the error from inverse transformation. We mainly use Monte Carlo method, which can be used to deal with kinds of transform function. In the third part, I have simulated logarithmic transformation to compare RMSE of Monte Carlo method and inverse. It can be see that Monte Carlo can decrease origin variable´s prediction error.
  • Keywords
    Monte Carlo methods; atmospheric techniques; disasters; meteorology; statistical analysis; Monte Carlo method; data products; disaster warning; logarithmic transformation; meteorology forecasting; model forecast value; observational data; statistical analysis; statistical modeling; transformed data prediction method; Data models; Educational institutions; Monte Carlo methods; Smoothing methods; Transforms; Weather forecasting; Monte Carlo; logit transform; origin variable forecast; relative humidify;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2011 International Conference on
  • Conference_Location
    Yichang
  • Print_ISBN
    978-1-4244-8162-0
  • Type

    conf

  • DOI
    10.1109/ICECENG.2011.6058256
  • Filename
    6058256