Analyzing the number of samples required for an approximate Monte-Carlo LMS line estimator

D. M. Mount, N. S. Netanyahu, E. Zuck

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This paper analyzes the number of samples required for an approximate Monte-Carlo least median of squares (LMS) line estimator. We provide a general computational framework, followed by detailed derivations for several point distributions and subsequent numerical results for the required number of samples.
Original languageAmerican English
Title of host publicationTheory and Applications of Recent Robust Methods
EditorsMia Hubert, Greet Pison, Anja Struyf, Stefan Van Aelst
PublisherBirkhäuser Basel
Pages207-219
ISBN (Print)978-3-0348-7958-3
StatePublished - 2004

Publication series

NameStatistics for Industry and Technology

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