Robust Regression: Asymptotics, Conjectures and Monte Carlo

Volume: 1, Issue: 5
Published: Sep 1, 1973
Abstract
Maximum likelihood type robust estimates of regression are defined and their asymptotic properties are investigated both theoretically and empirically. Perhaps the most important new feature is that the number pof parameters is allowed to increase with the number nof observations. The initial terms of a formal power series expansion (essentially in powers of p/n show an excellent agreement with Monte Carlo results, in most cases down to...
Paper Details
Title
Robust Regression: Asymptotics, Conjectures and Monte Carlo
Published Date
Sep 1, 1973
Volume
1
Issue
5
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.