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We consider nonparametric Bayesian estimation of a probability density p based on a random sample of size n from this density using a hierarchical prior. The prior consists, for instance, of prior wei...
For multivariate normal models and some exponential family models a multiple testing stepwise method is offered that is both admissible and consistent. The method is readily adaptable to selecting var...
In this paper, a new family of resampling-based penalization procedures for model selection is defined in a general framework. It generalizes several methods, including Efron's bootstrap penalization ...
This paper discusses a class of thresholding-based iterative selection procedures (TISP) for model selection and shrinkage. People have long before noticed the weakness of the convex $l_1$-constraint ...
Model selection is often performed by empirical risk minimization. The quality of selection in a given situation can be assessed by risk bounds, which require assumptions both on the margin and the ta...
This paper explores the following question: what kind of statistical guarantees can be given when doing variable selection in highdimensional models? In particular, we look at the error rates and p...
We revisit the problem of feature selection in linear discriminant analysis (LDA), i.e. when features are correlated. First, we introduce a pooled centroids formulation of the multi-class LDA predic...
We study partition distributions in a population genetics model incorporating symmetric selection and mutation. They generalize Ewens distributions in the infinitely-many-neutral-alleles model, an exp...
Let Y be a Gaussian vector whose components are independent with a common unknown variance. We consider the problem of estimating the mean μ of Y by model selection. More precisely, we start with a...
The estimation of cosmological parameters from precision observables is an important indus- try with crucial ramifications for particle physics. This article discusses the statistical methods presen...
Given a set-valued stochastic process (Vt)t=0,...,T, we say that the martingale selection problem is solvable if there exists an adapted sequence of selectors ξt in Vt, admitting an equivalent marting...
It is known that there is a dichotomy in the performance of model selectors. Those that are consistent (having the “oracle property”) do not achieve the asymptotic minimax rate for prediction error....
We introduce a new criterion to select in a consistent way the probabilistic context tree generating a sample. The basic idea is to construct a totally ordered set of candidate trees. This set is co...
A new influence measure is proposed to assess the influence of individual observations on prediction mean square errors (PMSE) in variable selection problems. It is based on the estimated PMSE which c...

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