- Volume 22, Number 2 (2016), 1131-1183.
Analysis of the Forward Search using some new results for martingales and empirical processes
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.
Bernoulli, Volume 22, Number 2 (2016), 1131-1183.
Received: February 2013
Revised: November 2014
First available in Project Euclid: 9 November 2015
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
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