Sensitivity Analysis in Semiparametric Regression Models

Wing-Kam Fung, Zhong-Yi Zhu and Bo-Cheng Wei
Additional contact information
Wing-Kam Fung: University of Hong Kong, Department of Statistics and Actuarial Science
Zhong-Yi Zhu: East China Normal University, Department of Statistics
Bo-Cheng Wei: Southeast University, Department of Mathematics

A chapter in Measurement and Multivariate Analysis, 2002, pp 233-240 from Springer

Abstract: Summary Research in semiparametric regression models has received attention in recent years. However, there is little work in the sensitivity analysis for such models. In this paper, we investigate the statistical diagnostics in semiparametric regression models. The case deletion influence diagnostics are constructed. An outlier diagnostic of the case deletion model is studied and it is shown to be equivalent to that of the mean-shift outlier model. The popular Cook’s distance is constructed which can be expressed in terms of the leverage measure and the residual. The proposed diagnostics are illustrated using a real data set.

Keywords: Royal Statistical Society; Spline Smoothing; Influential Observation; Partial Linear Model; Parametric Part (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-4-431-65955-6_25

Ordering information: This item can be ordered from
http://www.springer.com/9784431659556

DOI: 10.1007/978-4-431-65955-6_25

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().