ComputingA-optimal Designs for Weighted Polynomial Regression by Taylor Expansion
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Publication:5321961
DOI10.1080/03610920802610076zbMath1165.62051OpenAlexW2057453242MaRDI QIDQ5321961
Publication date: 16 July 2009
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610920802610076
Taylor expansionimplicit function theoremrecursive algorithm\(A\)-optimal designweighted polynomial regression\(A\)-equivalence theoremRemez's exchange procedure
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- A note on \(E\)-optimal designs for weighted polynomial regression
- Optimal weights for experimental designs on linearly independent support points
- Functional approach to optimal experimental design.
- Optimal designs for trigonometric and polynomial regression using canonical moments
- \(E\)-optimal designs for polynomial regression without intercept
- Remez's procedure for finding optimal designs
- \(E\)-optimal designs in weighted polynomial regression
- \(D\)-optimal designs for weighted polynomial regression
- Optimal designs for estimating individual coefficients in polynomial regression -- a functional approach
- Optimal designs for rational models and weighted polynomial regression
- A note on optimal designs in weighted polynomial regression for the classical efficiency functions
- \(E\)-optimal designs for polynomial regression
- \(D\)-optimal designs for weighted polynomial regression -- a functional approach
- Optimum Designs in Regression Problems
- The Equivalence of Two Extremum Problems
- Efficiency Problems in Polynomial Estimation
- Advanced Calculus with Applications in Statistics
- Optimal Experimental Designs
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