Influence analysis in response surface methodology

Yufen Huang, Chao Yen Hsieh

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The study of response surface methodology (RSM) involves both experimental planning and data modeling and analysis. Once a design is selected, and data obtained from it, models for representing the data need to be considered and fitted. During the fitting process, observations that are suspicious (e.g. outliers and/or influential points) may cause problems. Such observations need to be detected so that appropriate adjustments can be made to analysis. Thus far, the work on influence analysis of RSM is unexplored in statistical research. This will be the focus of this paper. We not only generalize the single perturbation scheme in Hampel's (1974) method, but also implement the pair-perturbation scheme in Huang et al. (2007a-c) to develop influence functions for sensitivity analysis in RSM. A simulation study and two real data examples for illustrating the effectiveness of the proposed method are provided.

Original languageEnglish
Pages (from-to)188-203
Number of pages16
JournalJournal of Statistical Planning and Inference
Volume147
DOIs
Publication statusPublished - 2014 Apr 1

Fingerprint

Influence Analysis
Response Surface Methodology
Perturbation
Influence Function
Data Modeling
Sensitivity analysis
Outlier
Sensitivity Analysis
Data structures
Data analysis
Adjustment
Planning
Simulation Study
Generalise
Response surface methodology
Observation
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

Cite this

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Influence analysis in response surface methodology. / Huang, Yufen; Hsieh, Chao Yen.

In: Journal of Statistical Planning and Inference, Vol. 147, 01.04.2014, p. 188-203.

Research output: Contribution to journalArticle

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