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Nonlinear Wavelet Shrinkage with Bayes Rules and Bayes Factors
Journal of the American Statistical Association, 1998Abstract Wavelet shrinkage, the method proposed by the seminal work of Donoho and Johnstone is a disarmingly simple and efficient way of denoising data. Shrinking wavelet coefficients was proposed from several optimality criteria. In this article a wavelet shrinkage by coherent Bayesian inference in the wavelet domain is proposed.
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Influence of groups of observations on bayes factors
Communications in Statistics - Theory and Methods, 1992A diagnostic for finding groups of observations influential on Bayes factors is discussed, which extends ideas in Pettit & Young (1990). Ways of reducing the combinatorial explosion involved in detecting more than one influential observation are considered. The effect of masking is also examined.
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Journal of the American Statistical Association, 1995
Robert E. Kass, Adrian E. Raftery
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Robert E. Kass, Adrian E. Raftery
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Parametric Empirical Bayes Inference: Theory and Applications
Journal of the American Statistical Association, 1983Carl N Morris
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Estimating a Population of Parameter Values Using Bayes and Empirical Bayes Methods
Journal of the American Statistical Association, 1984Thomas Louis
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