Minimizing the Condition Number to Construct Design Points for Polynomial Regression Models

DOI10.1137/110850268zbMath1274.62497OpenAlexW2094952253MaRDI QIDQ5300542

Julie Zhou, Jane J. Ye

Publication date: 27 June 2013

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/1f1656b9eae2895f0b362828da93f261bd295f2b

zbMATH Keywords

symmetric designinformation matrixsemidefinite programmingcondition numberpolynomial regression model\(K\)-optimal design

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Nonlinear programming (90C30) Numerical computation of matrix norms, conditioning, scaling (65F35)

Related Items (7)

D-optimal designs for complex Ornstein-Uhlenbeck processes ⋮ Condition Number Minimization in Euclidean Jordan Algebras ⋮ K-optimal designs for parameters of shifted Ornstein-Uhlenbeck processes and sheets ⋮ Constructing K-optimal designs for regression models ⋮ Weighted Approximate Fekete Points: Sampling for Least-Squares Polynomial Approximation ⋮ Least squares polynomial chaos expansion: a review of sampling strategies ⋮ K-Optimal Design via Semidefinite Programming and Entropy Optimization

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