Computational Algorithms for Calculating Least Absolute Value and Chebyshev Estimates for Multiple Regression
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Publication:3339238
DOI10.1080/01966324.1984.10737141zbMath0547.65098OpenAlexW2081449557WikidataQ58257483 ScholiaQ58257483MaRDI QIDQ3339238
Terry E. Dielman, Roger C. Pfaffenberger
Publication date: 1984
Published in: American Journal of Mathematical and Management Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/01966324.1984.10737141
least squares estimationmultiple regressionChebyshev estimationminimum absolute deviation estimation
Numerical smoothing, curve fitting (65D10) Linear regression; mixed models (62J05) Probabilistic methods, stochastic differential equations (65C99) Approximation by arbitrary linear expressions (41A45)
Related Items
Multivariate multiple linear regression based on the minimum sum of absolute errors criterion, A bootstrap approach to hypothesis testing in least absolute value regression, A note on hypothesis testing in LAV multiple regression: A small sample comparison, A note on hypothesis testing in LAV multiple regression: a small sample comparison, Least absolute value regression: recent contributions, Extensions to a Best Subset Algorithm for Least Absolute Value Estimation, A further comparison of tests of hypotheses in LAV regression, Algorithms for unconstrained \(L_ 1\) simple linear regression
Uses Software
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