TL;DRAbstract
We discuss the construction of minimax Bayesian T-optimal, D-ratio optimal and sequential G-optimal designs for discrimination between competing wavelet represen-tations of nonparametric regression models. In our examples we use the multiwavelet and Daubechies wavelet systems. We find that symmetry is an important property of designs for multiwavelet models, whereas designs for Daubechies wavelet models are nonsymmetric.
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We discuss the construction of minimax Bayesian T-optimal, D-ratio optimal and sequential G-optimal designs for discrimination between competing wavelet represen-tations of nonparametric regression models. In our examples we use the multiwavelet and Daubechies wavelet systems. We find that symmetry is an important property of designs for multiwavelet models, whereas designs for Daubechies wavelet models are nonsymmetric.
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