A partial-robust-ridge-based regression model with fuzzy predictors-responses

DOI10.1016/j.cam.2018.11.006zbMath1409.62140OpenAlexW2902027436WikidataQ128900597 ScholiaQ128900597MaRDI QIDQ1715825

Gholamreza Hesamian, Mohammad Ghasem Akbari

Publication date: 29 January 2019

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2018.11.006

zbMATH Keywords

kernel functionoutlierrobust estimationmulticollinearitygoodness-of-fit measurefuzzy coefficient\(\alpha\)-value

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Nonparametric robustness (62G35) Fuzziness, and linear inference and regression (62J86)

Related Items (7)

A fuzzy nonlinear univariate regression model with exact predictors and fuzzy responses ⋮ A fuzzy empirical quantile-based regression model based on triangular fuzzy numbers ⋮ A fuzzy linear regression model with autoregressive fuzzy errors based on exact predictors and fuzzy responses ⋮ A robust multiple regression model based on fuzzy random variables ⋮ A robust support vector regression with exact predictors and fuzzy responses ⋮ A robust varying coefficient approach to fuzzy multiple regression model ⋮ Fuzzy spline univariate regression with exact predictors and fuzzy responses

Uses Software

• robustbase

Cites Work

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