Bernoulli

  • Bernoulli
  • Volume 22, Number 2 (2016), 1131-1183.

Analysis of the Forward Search using some new results for martingales and empirical processes

Søren Johansen and Bent Nielsen

Full-text: Open access

Abstract

The Forward Search is an iterative algorithm for avoiding outliers in a regression analysis suggested by Hadi and Simonoff (J. Amer. Statist. Assoc. 88 (1993) 1264–1272), see also Atkinson and Riani (Robust Diagnostic Regression Analysis (2000) Springer). The algorithm constructs subsets of “good” observations so that the size of the subsets increases as the algorithm progresses. It results in a sequence of regression estimators and forward residuals. Outliers are detected by monitoring the sequence of forward residuals. We show that the sequences of regression estimators and forward residuals converge to Gaussian processes. The proof involves a new iterated martingale inequality, a theory for a new class of weighted and marked empirical processes, the corresponding quantile process theory, and a fixed point argument to describe the iterative aspect of the procedure.

Article information

Source
Bernoulli, Volume 22, Number 2 (2016), 1131-1183.

Dates
Received: February 2013
Revised: November 2014
First available in Project Euclid: 9 November 2015

Permanent link to this document
https://projecteuclid.org/euclid.bj/1447077772

Digital Object Identifier
doi:10.3150/14-BEJ689

Mathematical Reviews number (MathSciNet)
MR3449811

Zentralblatt MATH identifier
06562308

Keywords
fixed point result Forward Search iterated exponential martingale inequality quantile process weighted and marked empirical process

Citation

Johansen, Søren; Nielsen, Bent. Analysis of the Forward Search using some new results for martingales and empirical processes. Bernoulli 22 (2016), no. 2, 1131--1183. doi:10.3150/14-BEJ689. https://projecteuclid.org/euclid.bj/1447077772


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