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5 papers · 2 filters
A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing
Małgorzata Bogdan, Jayanta K. Ghosh, Surya T. Tokdar
In the spirit of modeling inference for microarrays as multiple testing for sparse mixtures, we present a similar approach to a simplified version of quantitative trait loci (QTL)…
Autoregressive Process Modeling via the Lasso Procedure
Yuval Nardi, Alessandro Rinaldo
The Lasso is a popular model selection and estimation procedure for linear models that enjoys nice theoretical properties. In this paper, we study the Lasso estimator for fitting a…
On the path density of a gradient field
Christopher R. Genovese, Marco Perone-Pacifico, Isabella Verdinelli +1
We consider the problem of reliably finding filaments in point clouds. Realistic data sets often have numerous filaments of various sizes and shapes. Statistical techniques exist f…
Properties and refinements of the fused lasso
Alessandro Rinaldo
We consider estimating an unknown signal, both blocky and sparse, which is corrupted by additive noise. We study three interrelated least squares procedures and their asymptotic pr…
Rodeo: Sparse, greedy nonparametric regression
John Lafferty, Larry Wasserman
We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimat…