A routine for converting regression algorithms into corresponding orthogonal regression algorithms

DOI10.1145/42288.42342zbMath0648.62069OpenAlexW2022739798MaRDI QIDQ3793557

Larry P. Ammann, John W. Van Ness

Publication date: 1988

Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)

Full work available at URL: http://www.acm.org/pubs/contents/journals/toms/1988-14/

zbMATH Keywords

robust regressionprincipal componentsrobust principal componentsL1 regressionregression algorithmserrors-in- variables regressionorthogonal regression algorithms

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Linear regression; mixed models (62J05) Probabilistic methods, stochastic differential equations (65C99)

Related Items (3)

Robust Principal Components ⋮ Standard and robust orthogonal regression ⋮ Maximum Lq-likelihood Estimation in Functional Measurement Error Models

This page was built for publication: A routine for converting regression algorithms into corresponding orthogonal regression algorithms