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Fuzzy sets in nonparametric Bayes regression

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 نشر من قبل Mohan Delampady
 تاريخ النشر 2008
  مجال البحث الاحصاء الرياضي
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A simple Bayesian approach to nonparametric regression is described using fuzzy sets and membership functions. Membership functions are interpreted as likelihood functions for the unknown regression function, so that with the help of a reference prior they can be transformed to prior density functions. The unknown regression function is decomposed into wavelets and a hierarchical Bayesian approach is employed for making inferences on the resulting wavelet coefficients.



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