Application of ridge regression and factor analysis in design and production of alloy wheels

DOI10.1080/02664763.2013.872233OpenAlexW2080263080MaRDI QIDQ5128655

Jianguo Li, Zhi-Sheng Ye, Mengru Zhang

Publication date: 28 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.872233

zbMATH Keywords

ridge regressionfactor analysisquality and reliabilitywheel production

Mathematics Subject Classification ID

Statistics (62-XX)

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Cites Work

• Unnamed Item
• Optimisation of ingot casting wheel design using SPH simulations
• A simulation study on SPSS ridge regression and ordinary least squares regression procedures for multicollinearity data
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• A Statistical View of Some Chemometrics Regression Tools
• Independent exploratory factor analysis with application to atmospheric science data
• Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression
• Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size
• Bayesian principal component regression with data-driven component selection
• Improved ridge estimators in a linear regression model
• Extending dual multiple factor analysis to categorical tables
• Some ridge regression estimators for the zero-inflated Poisson model
• The elements of statistical learning. Data mining, inference, and prediction