Hengzhen Huang

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A supersaturated design (SSD) is a design whose run size is not enough for estimating all the main effects. An important goal in the analysis of such designs is to identify active effects based on the effect sparsity assumption. A Bayesian variable selection strategy which combines the advantages of the componentwise Gibbs sampler (see Chen et al., 2011)(More)
This paper considers the problem of reconstructing a piecewise smooth model function from given, measured data. The data are compared to a field which is given as a possibly nonlinear function of the model. A regularization functional is added which incorporates the a pri-ori knowledge that the model function is piecewise smooth and may contain jump(More)
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