The Annals of Applied Statistics

最新文章

• 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...
• USE OF MULTIPLE SINGULAR VALUE DECOMPOSITIONS TO ANALYZE COMPLEX INTRACELLULAR CALCIUM ION SIGNALS AI翻译
  作者：Martinez, Josue G.; Huang, Jianhua Z.; Burghardt, Robert C.; Barhoumi, Rola; Carroll, Raymond J.
  作者单位：Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station
  摘要：We compare calcium ion signaling (Ca2+) between two exposures; the data are present as movies, or, more prosaically, time series of images. This paper describes novel uses of singular value decompositions (SVD) and weighted versions of them (WSVD) to extract the signals from such movies, in a way that is semi-automatic and tuned closely to the actual data and their many complexities. These complexities include the following. First, the images themselves are of no interest: all interest focuses...
• USING EPIDEMIC PREVALENCE DATA TO JOINTLY ESTIMATE REPRODUCTION AND REMOVAL AI翻译
  作者：van den Broek, Jan; Nishiura, Hiroshi
  作者单位：Utrecht University
  摘要：This study proposes a nonhomogeneous birth-death model which captures the dynamics of a directly transmitted infectious disease. Our model accounts for an important aspect of observed epidemic data in which only symptomatic infecteds are observed. The nonhomogeneous birth-death process depends on survival distributions of reproduction and removal, which jointly yield an estimate of the effective reproduction number R(t) as a function of epidemic time. We employ the Burr distribution family for...
• INTERPOLATING FIELDS OF CARBON MONOXIDE DATA USING A HYBRID STATISTICAL-PHYSICAL MODEL AI翻译
  作者：Malmberg, Anders; Arellano, Avelino; Edwards, David P.; Flyer, Natasha; Nychka, Doug; Wikle, Christopher
  作者单位：Ferring Pharmaceuticals; National Center Atmospheric Research (NCAR) - USA; National Center Atmospheric Research (NCAR) - USA
  摘要：Atmospheric Carbon Monoxide (CO) provides a window on the chemistry of the atmosphere since it is one of few chemical constituents that can be remotely sensed, and it can be used to determine budgets of other greenhouse gases Such as ozone and OH radicals. Remote sensing platforms in geostationary Earth orbit will soon provide regional observations of CO at several vertical layers with high spatial and temporal resolution. However, cloudy locations cannot be observed and estimates of the compl...