Using correlation coefficients to estimate slopes in multiple linear regression

DOI10.1007/s13571-010-0006-4zbMath1222.62087OpenAlexW1980100872MaRDI QIDQ717220

Rudy A. Gideon

Publication date: 29 September 2011

Published in: Sankhyā. Series B (Search for Journal in Brave)

Full work available at URL: https://scholarworks.umt.edu/math_pubs/5

zbMATH Keywords

Kendallnonparametricrank statisticsgreatest deviation correlation coefficient

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Linear regression; mixed models (62J05) Measures of association (correlation, canonical correlation, etc.) (62H20) Nonparametric tolerance and confidence regions (62G15)

Cites Work

• A Rank Correlation Coefficient Resistant to Outliers
• Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals
• Estimates of the Regression Coefficient Based on Kendall's Tau
• Unnamed Item

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