A Bayesian approach to flexible modeling of multivariable response functions

DOI10.1016/0047-259X(90)90033-EzbMath0711.62027MaRDI QIDQ923547

David M. Steinberg

Publication date: 1990

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

zbMATH Keywords

smoothingpolynomial regressionHermite polynomialsresponse functionpower series expansionprior distributionscomplete series expansionempirical regression modeling

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Bayesian inference (62F15) Linear inference, regression (62J99)

Related Items (2)

Improved inference in nonparametric regression using \(L_ k\)-smoothing splines ⋮ Comparison of designs for computer experiments

Uses Software

• Matlab

Cites Work

• Spline smoothing and optimal rates of convergence in nonparametric regression models
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Model robust response surface designs: Scaling two-level factorials
• A Bayesian approach to model inadequacy for polynomial regression
• Parametric Empirical Bayes Inference: Theory and Applications
• Notes on Generating Functions of Polynomials: (2) Hermite Polynomials
• A Bayesian approach to prediction using polynomials
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