On minimally-supported \(D\)-optimal designs for polynomial regression with log-concave weight function

DOI10.1007/s00184-006-0072-9zbMath1106.62077OpenAlexW1971793976MaRDI QIDQ870518

Hung-Ming Lin, Fu-Chuen Chang

Publication date: 12 March 2007

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00184-006-0072-9

zbMATH Keywords

Cyclic exchange algorithmGershgorin Circle TheoremLog-concaveMinimally-supported designWeighted polynomial regression

Mathematics Subject Classification ID

Related Items (3)

\(DS\)-optimal designs for random coefficient first-degree regression model with heteroscedastic errors ⋮ Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming‐Based Approach ⋮ Optimal Designs for Rational Function Regression

Uses Software

• Mathematica

Cites Work

• Logconcavity versus logconvexity: A complete characterization
• A note on optimal designs in weighted polynomial regression for the classical efficiency functions
• Log-concave probability and its applications
• \(D\)-optimal designs for weighted polynomial regression -- a functional approach
• The Equivalence of Two Extremum Problems
• The Coordinate-Exchange Algorithm for Constructing Exact Optimal Experimental Designs
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