Robust Box-Cox transformations based on minimum residual autocorrelation

DOI10.1016/j.csda.2005.04.007zbMath1445.62170OpenAlexW2063430264MaRDI QIDQ959359

Alfio Marazzi, Víctor J. Yohai

Publication date: 11 December 2008

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

Full work available at URL: https://doi.org/10.1016/j.csda.2005.04.007

zbMATH Keywords

heteroscedasticityrobust estimationBox-Cox transformation

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (4)

Evaluation of robust outlier detection methods for zero-inflated complex data ⋮ On Sensitivity of Inverse Response Plot Estimation and the Benefits of a Robust Estimation Approach ⋮ Robust fitting of claim severity distributions and the method of trimmed moments ⋮ Editorial: Machine learning and robust data mining

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• High breakdown-point and high efficiency robust estimates for regression
• Robust regression diagnostics with data transformations
• A non-parametric analysis of transformations
• On the optimality of S-estimators
• Robust diagnostic regression analysis
• Bootstrapping robust estimates of regression
• The Analysis of Transformed Data
• An Analysis of Transformations Revisited
• Transforming a response variable for linearity
• Estimation for the Box-Cox Transformation Model Without Assuming Parametric Error Distribution
• Robust Estimation of a Location Parameter

This page was built for publication: Robust Box-Cox transformations based on minimum residual autocorrelation