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A simple and numerical stable algorithm for solving the cone projection problem based on a Gram-Schmidt process
cone projection algorithm convexity constraints convexity test simulations Gram-Schmidt
2012/9/19
We are presenting a simple and numerical stable algorithm for the solution of the cone projection problem which is suitable for relative small data sets and for simulation purposes needed for con-vexi...
Local superefficiency of data-driven projection density estimators in continuous time
Density estimation data-driven superefficiency continuous time processes
2009/2/23
We construct a data-driven projection density estimator for continuous time processes. This estimator reaches superoptimal rates over a class F0 of densities that is dense in the family of all possibl...
Bayesian projection approaches to variable selection and exploring model uncertainty
Bayesian variable selection Kullback-Leibler projection lasso non-negative garotte preconditioning
2010/3/17
A Bayesian approach to variable selection which is based on the expected Kullback-
Leibler divergence between the full model and its projection onto a submodel has
recently been suggested in the lit...
Multidimensional trimming based on projection depth
Projection depth depth regions directional radius multivariatetrimmed means influence function breakdown point
2010/4/26
As estimators of location parameters, univariate trimmed means
are well known for their robustness and efficiency. They can serve
as robust alternatives to the sample mean while possessing high effi...