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文章基本信息

  • 标题:Smoothing with Mixed Model Software
  • 本地全文:下载
  • 作者:Long Ngo ; Matthew P. Wand
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2004
  • 卷号:9
  • 期号:1
  • 页码:1-54
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:Smoothing methods that use basis functions with penalization can be formulated as fits in a mixed model framework. One of the major benefits is that software for mixed model analysis can be used for smoothing. We illustrate this for several smoothing models such as additive and varying coefficient models for both S-PLUS and SAS software. Code for each of the illustrations is available on the Internet.
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