Influence diagnostics and outlier tests for varying coefficient mixed models

Zaixing Li, Wangli Xu, Lixing ZHU*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

In this paper, we consider subset deletion diagnostics for fixed effects (coefficient functions), random effects and one variance component in varying coefficient mixed models (VCMMs). Some simple updated formulas are obtained, and based on which, Cook's distance, joint influence and conditional influence are also investigated. Besides, since mean shift outlier models (MSOMs) are also efficient to detect outliers, we establish an equivalence between deletion models and MSOMs, which is not only suitable for fixed effects but also for random effects, and test statistics for outliers are then constructed. As a byproduct, we obtain the nonparametric "delete = replace" identity. Our influence diagnostics methods are illustrated through a simulated example and a real data set.

Original languageEnglish
Pages (from-to)2002-2017
Number of pages16
JournalJournal of Multivariate Analysis
Volume100
Issue number9
DOIs
Publication statusPublished - Oct 2009

Scopus Subject Areas

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

User-Defined Keywords

  • "Delete=Replace" identity
  • Conditional influence
  • Cook's distance
  • Influence diagnostics
  • Joint influence
  • Outlier tests

Fingerprint

Dive into the research topics of 'Influence diagnostics and outlier tests for varying coefficient mixed models'. Together they form a unique fingerprint.

Cite this