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    題名: Spatial Distribution of Taiwan Air Pollutant-An Application of Spatial Quantile Regression, The 28th International Biometric Conference
    作者: Chang, Y.-M
    關鍵詞: air pollution;spatial temporal data;quantile regression;variable selection;Lasso
    日期: 2016-08-11
    上傳時間: 2018-02-03 02:10:35 (UTC+8)
    摘要: Many literatures have pointed out that air pollutants increase morbidity risks of a number of diseases. It would affect the growth ofnational health expense . In this research, we are interested in estimating quantiles of air pollutants. The quantile is decomposed as a linear combination of basis functions. The quantile regression method is used to demonstrate the spatial distribution of air pollutants in different months. A subset selection method of Lasso is used to choose a suitable subset of the basis functions and estimate corresponding parameters. This method is computationally efficient for large data sets.
    關聯: 第十屆海峽兩岸統計與概率研討會
    顯示於類別:[統計學系暨研究所] 會議論文

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