Statistical modelling via dimension reduction methods

DOI10.1016/S0362-546X(97)00349-0zbMath1090.62549MaRDI QIDQ4374251

Jane-Ling Wang, Yun Sam Chong

Publication date: 1997

Published in: Nonlinear Analysis: Theory, Methods & Applications (Search for Journal in Brave)

zbMATH Keywords

smoothingprojection pursuitprincipal componentssliced inverse regressionalternating conditional expectationbackfitting algorithmAdditive models

Mathematics Subject Classification ID

Linear inference, regression (62J99)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On almost linearity of low dimensional projections from high dimensional data
• On projection pursuit regression
• The dimensionality reduction principle for generalized additive models
• Additive regression and other nonparametric models
• Generalized additive models
• Slicing regression: A link-free regression method
• Multivariate adaptive regression splines
• Estimation of a projection-pursuit type regression model
• Optimal smoothing in single-index models
• Exploring Regression Structure Using Nonparametric Functional Estimation
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Estimating Optimal Transformations for Multiple Regression and Correlation
• Flexible Parsimonious Smoothing and Additive Modeling
• Sliced Inverse Regression for Dimension Reduction
• On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
• Determining the Dimensionality in Sliced Inverse Regression
• Reweighting to Achieve Elliptically Contoured Covariates in Regression
• A Projection Pursuit Algorithm for Exploratory Data Analysis
• Comment