.png){kind=icon}
返回
Robust continuum regression
.png){kind=icon}
OA
AI
DOI：10.1016/j.chemolab.2004.11.002.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Several applications of continuum regression (CR) to non-contaminated data have shown that a significant improvement in predictive power can be obtained compared to the three standard techniques which it encompasses (ordinary least squares (OLS), principal component regression (PCR) and partial least squares (PLS)). For contaminated data continuum regression may yield aberrant estimates due to its non-robustness with respect to outliers. Also for data originating from a distribution which significantly differs from the normal distribution, continuum regression may yield very inefficient estimates. In the current paper, robust continuum regression (RCR) is proposed. To construct the estimator, an algorithm based on projection pursuit (PP) is proposed. The robustness and good efficiency properties of RCR are shown by means of a simulation study. An application to an X-ray fluorescence analysis of hydrometallurgical samples illustrates the method's applicability in practice. (c) 2004 Elsevier B.V. All rights reserved.
Keyword:
continuum regression (CR)
Projection pursuit
robust continuum regression (RCR)
robust multivariate calibration
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.8
论文数:
4.6K
被引数:
1.2W
机构
暂无机构信息
引用论文
ROLE OF HYDROGEN CHLORIDE IN HOT-SALT STRESS CORROSION CRACKING OF TITANIUM- -ALUMINUM ALLOYS..png)
OAAI
IF0
OAAI分享收藏分享收藏
查看更多内容