A segmentation-based algorithm for large-scale partially ordered monotonic regression

DOI10.1016/j.csda.2011.03.001zbMath1464.62169OpenAlexW2107802976MaRDI QIDQ1658336

A. Grimvall, Oleg P. Burdakov, Oleg Sysoev

Publication date: 14 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.03.001

zbMATH Keywords

quadratic programminglarge-scale optimizationmonotonic regressionpool-adjacent-violators algorithmleast distance problempartially ordered data set

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Quadratic programming (90C20)

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Characterizing the optimal solutions to the isotonic regression problem for identifiable functionals ⋮ Bootstrap Confidence Intervals for Large-scale Multivariate Monotonic Regression Problems ⋮ A dual active-set algorithm for regularized monotonic regression ⋮ Monotonicity recovering and accuracy preserving optimization methods for postprocessing finite element solutions ⋮ Isotonic regression for multiple independent variables ⋮ Generalized isotonized mean estimators for judgment post-stratification with multiple rankers

Cites Work

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