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that, for neighborhood selection in Gaussian graphical models, under a neighborhood stability condition, the LASSO is consistent, even when the number of variables is of greater order than the sample size. Zhao and Yu [(2006) J. Machine Learning Research 7 2541–2567] formalized the neighborhood stability condition in the context of linear regression as a(More)
1 Summary. We study the asymptotic properties of adaptive LASSO estimators in sparse, high-dimensional, linear regression models when the number of covariates may increase with the sample size. We consider variable selection using the adaptive LASSO, where the L 1 norms in the penalty are re-weighted by data-dependent weights. We show that, if a reasonable(More)
Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the(More)
Context-aware computing is an emerging computing paradigm that can provide new or improved services by exploiting user context information. In this paper, we present a wireless-local-area-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a position-determination model to gather location information from collected WLAN(More)
1 Summary. We study the asymptotic properties of bridge estimators in sparse, high-dimensional, linear regression models when the number of covariates may increase to infinity with the sample size. We are particularly interested in the use of bridge estima-tors to distinguish between covariates whose coefficients are zero and covariates whose coefficients(More)
A number of variable selection methods have been proposed involving nonconvex penalty functions. These methods, which include the smoothly clipped absolute deviation (SCAD) penalty and the minimax concave penalty (MCP), have been demonstrated to have attractive theoretical properties, but model fitting is not a straightforward task, and the resulting(More)
Repetitive stimulation potentiates contractile tension of fast-twitch skeletal muscle. We examined the role of myosin regulatory light chain (RLC) phosphorylation in this physiological response by ablating Ca(2+)/calmodulin-dependent skeletal muscle myosin light chain kinase (MLCK) gene expression. Western blot and quantitative-PCR showed that MLCK is(More)
This paper evaluates and compares four volume rendering algorithms that have become rather popular for rendering datasets described on uniform rectilinear grids: raycasting, splatting, shear-warp, and hardware-assisted 3D texture-mapping. In order to assess both the strengths and the weaknesses of these algorithms in a wide variety of scenarios, a set of(More)
In many applications, covariates possess a grouping structure that can be incorporated into the analysis to select important groups as well as important members of those groups. This work focuses on the incorporation of grouping structure into penalized regression. We investigate the previously proposed group lasso and group bridge penalties as well as a(More)