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
Link To Document