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连续谱数据的函数型主成分回归

黄乐乐 王惠文 朱嘉

黄乐乐, 王惠文, 朱嘉等 . 连续谱数据的函数型主成分回归[J]. 北京航空航天大学学报, 2014, 40(6): 792-796. doi: 10.13700/j.bh.1001-5965.2013.0409
引用本文: 黄乐乐, 王惠文, 朱嘉等 . 连续谱数据的函数型主成分回归[J]. 北京航空航天大学学报, 2014, 40(6): 792-796. doi: 10.13700/j.bh.1001-5965.2013.0409
Huang Lele, Wang Huiwen, Zhu Jiaet al. Functional principal component regression for continuous spectra data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(6): 792-796. doi: 10.13700/j.bh.1001-5965.2013.0409(in Chinese)
Citation: Huang Lele, Wang Huiwen, Zhu Jiaet al. Functional principal component regression for continuous spectra data[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(6): 792-796. doi: 10.13700/j.bh.1001-5965.2013.0409(in Chinese)

连续谱数据的函数型主成分回归

doi: 10.13700/j.bh.1001-5965.2013.0409
基金项目: 

国家自然科学基金资助项目(71031001,20903013);北京航空航天大学博士研究生创新基金资助项目(YWF-14-YJSY-027)

详细信息
    作者简介:

    黄乐乐(1986- ),男,河南济源人,博士生,nanhuabiren@163.com.

  • 中图分类号: O212

Functional principal component regression for continuous spectra data

  • 摘要: 对连续谱数据不做离散化处理,而是将光滑后的连续谱作为连续曲线,进行函数型主成分回归分析,以期获得既可降维又能减少信息损失的回归方程.在此建模过程中,还引入连续谱的导数曲线作为协变量,并给出函数型主成分回归系数的bootstrap置信区间.作为实证研究,对玻璃样品的X射线谱和样品中硅元素含量进行回归分析.研究结果表明,基于函数型主成分的回归分析对响应变量具有较强解释能力,同时其回归系数更加符合数据本身的特点,显示出新方法所具有的优越性与实用价值.

     

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  • 被引次数: 0
出版历程
  • 收稿日期:  2013-07-02
  • 网络出版日期:  2014-06-20

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