on the basis of their commonly known strength levels, and privately observed strengthshocks

We consider a general nonparametric regression model called the compound model. It includes, as special cases, sparse additive regression and nonparametric (or linear) regression with many covariates but possibly a small number of relevant covariates. The compound model is characterized by three...

We consider the problem of estimating a sparse linear regression vector under a gaussiannoise model, for the purpose of both prediction and model selection. We assume that priorknowledge is available on the sparsity pattern, namely the set of variables is partitioned intoprescribed groups, only...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given dataset, a statistical test is required. In this paper, we develop such a test based on the linear state space representation. We provide a...