Assessing local influence in PLS regression by the second order approach

✍ Scribed by Bo Cheng; Xizhi Wu

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 130 KB
• Volume: 53
• Category: Article
• ISSN: 0167-7152
• DOI: 10.1016/s0167-7152(01)00010-4

✦ Synopsis

Partial least squares (PLS) regression has received increasing attention in recent years. However, like other regression methods, PLS ÿtting could be substantially altered by one or a few in uential points. This paper assesses the local in uence by examining the second order derivatives on certain perturbed parameter surfaces related to statistics of interest such as criterion Q and the estimated coe cients ÿ. We also illustrate our idea via a numerical example, where the masking phenomenon is present.