2009

最新文章

• g-SELC: OPTIMIZATION BY SEQUENTIAL ELIMINATION OF LEVEL COMBINATIONS USING GENETIC ALGORITHMS AND GAUSSIAN PROCESSES AI翻译
  作者：Mandal, Abhyuday; Ranjan, Pritam; Wu, C. F. Jeff
  作者单位：University System of Georgia; University of Georgia; Acadia University; University System of Georgia; Georgia Institute of Technology
  摘要：Identifying promising compounds from a vast collection of feasible compounds is an important and yet challenging problem in the pharmaceutical industry. An efficient solution to this problem will help reduce the expenditure at the early stages of drug discovery. In an attempt to solve this problem, Mandal, Wu and Johnson [Technometrics 48 (2006) 273-283] proposed the SELC algorithm. Although powerful, it fails to extract substantial information from the data to guide the search efficiently, as...
• A NEW LATENT CURE RATE MARKER MODEL FOR SURVIVAL DATA AI翻译
  作者：Kim, Sungduk; Xi, Yingmei; Chen, Ming-Hui
  作者单位：National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD); Biogen; University of Connecticut
  摘要：To address an important risk classification issue that arises in clinical practice, we propose a new mixture model via latent cure rate markers for survival data with a cure fraction. In the proposed model, the latent cure rate markers are modeled via a multinomial logistic regression and patients who share the same cure rate are classified into the same risk group. Compared to available cure rate models, the proposed model fits better to data from a prostate cancer clinical trial. In addition...
• PREDICTION OF REMAINING LIFE OF POWER TRANSFORMERS BASED ON LEFT TRUNCATED AND RIGHT CENSORED LIFETIME DATA AI翻译
  作者：Hong, Yili; Meeker, William Q.; McCalley, James D.
  作者单位：Iowa State University; Iowa State University
  摘要：Prediction of the remaining life of high-voltage power transformers is an important issue for energy companies because of the need for planning maintenance and capital expenditures. Lifetime data for such transformers are complicated because transformer lifetimes can extend over many decades and transformer designs and manufacturing practices have evolved. We were asked to develop statistically-based predictions for the lifetimes of an energy company's fleet of high-voltage transmission and di...
• TIME SERIES ANALYSIS VIA MECHANISTIC MODELS AI翻译
  作者：Breto, Carles; He, Daihai; Ionides, Edward L.; King, Aaron A.
  作者单位：Universidad Carlos III de Madrid; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：The purpose of time series analysis via mechanistic models is to reconcile the known or hypothesized structure of a dynamical system with observations collected over time. We develop a framework for Constructing nonlinear mechanistic models and carrying Out inference. Our framework permits the consideration of implicit dynamic models, meaning statistical models for stochastic dynamical systems which are specified by a simulation algorithm to generate sample paths. Inference procedures that ope...
• DISCUSSION OF: BROWNIAN DISTANCE COVARIANCE AI翻译
  作者：Gretton, Arthur; Fukumizu, Kenji; Sriperumbudur, Bharath K.
  作者单位：Carnegie Mellon University; Max Planck Society; Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan; University of California System; University of California San Diego; Max Planck Society; University of California System; University of California San Diego
• STRUCTURED VARIABLE SELECTION AND ESTIMATION AI翻译
  作者：Yuan, Ming; Joseph, V. Roshan; Zou, Hui
  作者单位：University System of Georgia; Georgia Institute of Technology; University of Minnesota System; University of Minnesota Twin Cities
  摘要：In linear regression problems with related predictors, it is desirable to do variable selection and estimation by maintaining the hierarchical or structural relationships among predictors. In this paper we propose non-negative garrote methods that can naturally incorporate such relationships defined through effect heredity principles or marginality principles. We show that the methods are very easy to compute and enjoy nice theoretical properties. We also show that the methods can be easily ex...
• FINDING LARGE AVERAGE SUBMATRICES IN HIGH DIMENSIONAL DATA AI翻译
  作者：Shabalin, Andrey A.; Weigman, Victor J.; Perou, Charles M.; Nobel, Andrew B.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
  摘要：The search for sample-variable associations is an important problem in the exploratory analysis of high dimensional data. Biclustering methods search for sample-variable associations in the form of distinguished submatrices of the data matrix. (The rows and columns of a submatrix need not be contiguous.) In this paper we propose and evaluate a statistically motivated biclustering procedure (LAS) that finds large average submatrices within a given real-valued data matrix. The procedure operates...
• PRACTICAL LARGE-SCALE SPATIO-TEMPORAL MODELING OF PARTICULATE MATTER CONCENTRATIONS AI翻译
  作者：Paciorek, Christopher J.; Yanosky, Jeff D.; Puett, Robin C.; Laden, Francine; Suh, Helen H.
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; University of South Carolina System; University of South Carolina Columbia; University of South Carolina System; University of South Carolina Columbia; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital; Harvard University; Harvard Medical School; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. W...
• BROWNIAN DISTANCE COVARIANCE AI翻译
  作者：Szekely, Gabor J.; Rizzo, Maria L.
  作者单位：University System of Ohio; Bowling Green State University; Hungarian Academy of Sciences; HUN-REN; HUN-REN Alfred Renyi Institute of Mathematics
  摘要：Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with respect to a stochast...
• DERIVING CHEMOSENSITIVITY FROM CELL LINES: FORENSIC BIOINFORMATICS AND REPRODUCIBLE RESEARCH IN HIGH-THROUGHPUT BIOLOGY AI翻译
  作者：Baggerly, Keith A.; Coombes, Kevin R.
  作者单位：University of Texas System; UTMD Anderson Cancer Center
  摘要：High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, however, is often not described well enough to allow for exact reproduction of the results, leading to exercises in forensic bioinformatics where aspects of raw data and reported results are used to infer what methods must have been employed. Unfortunately, poor documentation can shift from an inconvenience to an active...