2期

最新文章

• LENGTH-BIASED SEMICOMPETING RISKS MODELS FOR CROSS-SECTIONAL DATA: AN APPLICATION TO CURRENT DURATION OF PREGNANCY ATTEMPT DATA AI翻译
  作者：McLain, Alexander C.; Guo, Siyuan; Thoma, Marie; Zhang, Jiajia
  作者单位：University of South Carolina System; University of South Carolina Columbia; University System of Maryland; University of Maryland College Park
  摘要：Cross-sectional length-biased data arise from questions on the at-risk time for an event of interest from those who are at risk but have yet to experience the event. For example, in the National Survey on Family Growth (NSFG) women, who were currently attempting to become pregnant, were asked how long they had been attempting pregnancy. Cross-sectional survival analysis methods use the observed at-risk times to make inference on the distribution of the unobserved time-to-failure. However, meth...
• LEARNING EXCURSION SETS OF VECTOR-VALUED GAUSSIAN RANDOM FIELDS FOR AUTONOMOUS OCEAN SAMPLING AI翻译
  作者：Fossum, Trygve Olav; Travelletti, Cedric; Eidsvik, Jo; Ginsbourger, David; Rajan, Kanna
  作者单位：Norwegian University of Science & Technology (NTNU); University of Bern; Norwegian University of Science & Technology (NTNU); Universidade do Porto
  摘要：Improving and optimizing oceanographic sampling is a crucial task for marine science and maritime resource management. Faced with limited resources in understanding processes in the water column, the combination of statistics and autonomous systems provides new opportunities for experimental design. In this work we develop efficient spatial sampling methods for characterizing regions, defined by simultaneous exceedances above prescribed thresholds of several responses, with an application focu...
• A BAYESIAN NONPARAMETRIC MODEL FOR INFERRING SUBCLONAL POPULATIONS FROM STRUCTURED DNA SEQUENCING DATA AI翻译
  作者：He, Shai; Schein, Aaron; Sarsani, Vishal; Flaherty, Patrick
  作者单位：University of Massachusetts System; University of Massachusetts Amherst; Columbia University
  摘要：There are distinguishing features or hallmarks of cancer that are found across tumors, individuals and types of cancer, and these hallmarks can be driven by specific genetic mutations. Yet within a single tumor there is often extensive genetic heterogeneity as evidenced by single-cell and bulk DNA sequencing data. The goal of this work is to jointly infer the underlying genotypes of tumor subpopulations and the distribution of those subpopulations in individual tumors by integrating single-cel...
• A COMPOSITIONAL MODEL TO ASSESS EXPRESSION CHANGES FROM SINGLE-CELL RNA-SEQ DATA AI翻译
  作者：Ma, Xiuyu; Korthauer, Keegan; Kendziorski, Christina; Newton, Michael A.
  作者单位：University of Wisconsin System; University of Wisconsin Madison; University of British Columbia; University of Wisconsin System; University of Wisconsin Madison
  摘要：On the problem of scoring genes for evidence of changes in the distribution of single-cell expression, we introduce an empirical Bayesian mixture approach and evaluate its operating characteristics in a range of numerical experiments. The proposed approach leverages cell-subtype structure revealed in cluster analysis in order to boost gene-level information on expression changes. Cell clustering informs gene-level analysis through a specially-constructed prior distribution over pairs of multin...
• EFFICIENT BAYESIAN INFERENCE OF GENERAL GAUSSIAN MODELS ON LARGE PHYLOGENETIC TREES AI翻译
  作者：Bastide, Paul; Ho, Lam Si Tung; Baele, Guy; Lemey, Philippe; Suchard, Marc A.
  作者单位：Universite de Montpellier; Centre National de la Recherche Scientifique (CNRS); Dalhousie University; KU Leuven; California State University System; California State University Los Angeles; California State University System; California State University Los Angeles; California State University System; California State University Los Angeles
  摘要：Phylogenetic comparative methods correct for shared evolutionary history among a set of nonindependent organisms by modeling sample traits as arising from a diffusion process along the branches of a possibly unknown history. To incorporate such uncertainty, we present a scalable Bayesian inference framework under a general Gaussian trait evolution model that exploits Hamiltonian Monte Carlo (HMC). HMC enables efficient sampling of the constrained model parameters and takes advantage of the tre...
• A BAYESIAN SEMIPARAMETRIC JOLLY-SEBER MODEL WITH INDIVIDUAL HETEROGENEITY: AN APPLICATION TO MIGRATORY MALLARDS AT STOPOVER AI翻译
  作者：Wu, Guohui; Holan, Scott H.; Avril, Alexis; Waldenstrom, Jonas
  作者单位：SAS Institute Inc; University of Missouri System; University of Missouri Columbia; Linnaeus University
  摘要：We propose a Bayesian hierarchical Jolly-Seber model that can accommodate a semiparametric functional relationship between external covariates and capture probabilities, individual heterogeneity in departure due to an internal time-varying covariate and the dependence of arrival time on external covariates. Modelwise, we consider a stochastic process to characterize the evolution of the partially observable internal covariate that is linked to departure probabilities. Computationally, we devel...
• ESTIMATING HIGH-RESOLUTION RED SEA SURFACE TEMPERATURE HOTSPOTS, USING A LOW-RANK SEMIPARAMETRIC SPATIAL MODEL AI翻译
  作者：Hazra, Arnab; Huser, Raphael
  作者单位：King Abdullah University of Science & Technology
  摘要：In this work, we estimate extreme sea surface temperature (SST) hotspots, that is, high threshold exceedance regions, for the Red Sea, a vital region of high biodiversity. We analyze high-resolution satellite-derived SST data comprising daily measurements at 16,703 grid cells across the Red Sea over the period 1985-2015. We propose a semiparametric Bayesian spatial mixed-effects linear model with a flexible mean structure to capture spatially-varying trend and seasonality, while the residual s...
• A CONTINUOUS-TIME SEMI-MARKOV MODEL FOR ANIMAL MOVEMENT IN A DYNAMIC ENVIRONMENT AI翻译
  作者：Johnson, Devin; Pelland, Noel; Sterling, Jeremy
  作者单位：National Oceanic Atmospheric Admin (NOAA) - USA
  摘要：We consider an extension to discrete-space, continuous-time models for animal movement that have previously been presented in the literature. The extension from a continuous-time Markov formulation to a continuous-time semi-Markov formulation allows for the inclusion of temporally dynamic habitat conditions as well as temporally changing movement responses by animals to that environment. We show that, with only a little additional consideration, the Poisson likelihood calculation for the Marko...
• SCALABLE PENALIZED SPATIOTEMPORAL LAND-USE REGRESSION FOR GROUND-LEVEL NITROGEN DIOXIDE AI翻译
  作者：Messier, Kyle P.; Katzfuss, Matthias
  作者单位：National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS); Texas A&M University System; Texas A&M University College Station
  摘要：Nitrogen dioxide (NO2) is a primary constituent of traffic-related air pollution and has well-established harmful environmental and human-health impacts. Knowledge of the spatiotemporal distribution of NO2 is critical for exposure and risk assessment. A common approach for assessing air pollution exposure is linear regression involving spatially referenced covariates, known as land-use regression (LUR). We develop a scalable approach for simultaneous variable selection and estimation of LUR mo...
• A BRIDGING MODEL TO RECONCILE STATISTICS BASED ON DATA FROM MULTIPLE SURVEYS AI翻译
  作者：Erciulescu, Andreea L.; Opsomer, Jean D.; Breidt, F. Jay
  作者单位：Westat; Colorado State University System; Colorado State University Fort Collins
  摘要：Surveys designed to collect data on similar variables using samples representing the same population may still result in different estimates due, for example, to differences in sample designs or modes of data collection. Considered in this paper is the case where two surveys were conducted concurrently, with one using the same methodology as used in prior rounds of the survey and the other using an updated methodology, resulting in substantial differences in several key estimates. Due to diffe...