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We study the asymptotic properties of the 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 L1 norms in the penalty are re-weighted by data-dependent weights. We show that, if a reasonable initial(More)
We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is "small" relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are(More)
The common single-threaded execution model limits processors to exploiting only the relatively small amount of instruction-level parallelism available in application programs. The superthreaded processor, on the other hand, is a concurrent multithreaded architecture (CMA) that can exploit the multiple granularities of parallelism available in(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)
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-localarea-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a positiondetermination model to gather location information from collected WLAN(More)
Memcached is a key-value distributed memory object caching system. It is used widely in the data-center environment for caching results of database calls, API calls or any other data. Using Memcached, spare memory in data-center servers can be aggregated to speed up lookups of frequently accessed information. The performance of Memcached is directly related(More)
The partly linear additive Cox model is an extention of the (linear) Cox model and allows flexible modeling of covariate effects semiparametrically. We study asymptotic properties of the maximum partial likelihood estimator of this model with right-censored data using polynomial splines. We show that, with a range of choices of the smoothing parameter (the(More)
We used expression quantitative trait locus mapping in the laboratory rat (Rattus norvegicus) to gain a broad perspective of gene regulation in the mammalian eye and to identify genetic variation relevant to human eye disease. Of >31,000 gene probes represented on an Affymetrix expression microarray, 18,976 exhibited sufficient signal for reliable analysis(More)
SMP clusters and multiclusters are widely used to execute message-passing parallel applications. The ways to map parallel processes to processors (or cores) could affect the application performance significantly due to the non-uniform communicating cost in such systems. It is desired to have a tool to map parallel processes to processors (or cores)(More)