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SLOPE-ADAPTIVE VARIABLE SELECTION VIA CONVEX OPTIMIZATION.
TLDR
SLOPE, short for Sorted L-One Penalized Estimation, is the solution to λBH and appears to have appreciable inferential properties under more general designs X while having substantial power, as demonstrated in a series of experiments running on both simulated and real data. Expand
Modifying the Schwarz Bayesian Information Criterion to Locate Multiple Interacting Quantitative Trait Loci
TLDR
This work investigates the behavior of the Schwarz Bayesian information criterion (BIC) by explaining the phenomenon of the overestimation and proposing a novel modification of BIC that allows the detection of main effects and pairwise interactions in a backcross population. Expand
Asymptotic Bayes-optimality under sparsity of some multiple testing procedures
Within a Bayesian decision theoretic framework we investigate some asymptotic optimality properties of a large class of multiple testing rules. A parametric setup is considered, in which observationsExpand
Statistical estimation and testing via the sorted L1 norm
We introduce a novel method for sparse regression and variable selection, which is inspired by modern ideas in multiple testing. Imagine we have observations from the linear model y = X beta + z,Expand
False Discoveries Occur Early on the Lasso Path
TLDR
It is demonstrated that true features and null features are always interspersed on the Lasso path, and that this phenomenon occurs no matter how strong the effect sizes are. Expand
A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing
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) mapping. Unlike inExpand
Data Driven Smooth Tests for Bivariate Normality
Based upon the idea of construction of data driven smooth tests for composite hypotheses presented in Inglotet al.(1997) and Kallenberg and Ledwina (1997), two versions of data driven smooth test forExpand
On Locating Multiple Interacting Quantitative Trait Loci in Intercross Designs
TLDR
The proposed methods by computer simulations under a wide range of realistic genetic models, with nonequidistant marker spacings and missing data, demonstrate good properties of the proposed method of QTL detection. Expand
Controlling the Rate of GWAS False Discoveries
TLDR
This work proposes a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses and shows how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. Expand
A Data Driven Smooth Test for Circular Uniformity
We propose a new omnibus test for uniformity on the circle. The new test is based upon the idea of data driven smooth tests as presented in Ledwina (1994, J. Amer. Statist. Assoc., 89, 1000–1005).Expand
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