Scholarlink

<p>We introduce a robust variant of smoothing spline regression which exploits an entropy-based argument to automatically detect and remove outliers during the fitting procedure. This involves considering a penalized weighted residual sum of squares, with the distribution of weights determined by maximizing the associated entropy function. An illustrative example is provided to show the potential of the new approach compared to other standard robust techniques. Additionally, we include examples on datasets derived from real-world applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A robust variant of cubic smoothing spline approximation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月9日

查看全文
  • Marcello De Giosa,
  • Antonella Falini,
  • Felice Iavernaro,
  • Susanna Losito,
  • Francesca Mazzia,
  • Giorgia Rubino

摘要

We introduce a robust variant of smoothing spline regression which exploits an entropy-based argument to automatically detect and remove outliers during the fitting procedure. This involves considering a penalized weighted residual sum of squares, with the distribution of weights determined by maximizing the associated entropy function. An illustrative example is provided to show the potential of the new approach compared to other standard robust techniques. Additionally, we include examples on datasets derived from real-world applications.