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Principal components analysis (PCA) is a classical method for the reduction of dimensionality of data in the form of n observations (or cases) of a vector with p variables. Contemporary data sets of...
Wavelets have motivated development of a host of new ideas in nonparametric regression smoothing. Here we apply the tool of exact risk analysis, to understand the small sample behavior of wavelet es...
The Hudson River is a strongly heterotrophic system in which the invasive zebra mussel (Dreissena polymorpha) comprises >90% of total metazoan biomass. Using a Bayesian mixing model, with isotope rati...
A tractable nonparametric prior over densities is introduced which is closed under sampling and exhibits proper posterior asymptotics.
We derive the Jeffreys prior for the parameter of the Multivariate Ewens Distribution and study some of its properties. In particular, we show that this prior is proper and has no finite moments. We a...

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