The Annals of Applied Statistics

最新文章

• A SIMULATION-BASED FRAMEWORK FOR ASSESSING THE FEASIBILITY OF RESPONDENT-DRIVEN SAMPLING FOR ESTIMATING CHARACTERISTICS IN POPULATIONS OF LESBIAN, GAY AND BISEXUAL OLDER ADULTS AI翻译
  作者：Griffin, Maryclare; Gile, Krista J.; Fredricksen-Goldsen, Karen, I; Handcock, Mark S.; Erosheva, Elena A.
  作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Massachusetts System; University of Massachusetts Amherst; University of California System; University of California Los Angeles
  摘要：Respondent-driven sampling (RDS) is a method for sampling from a target population by leveraging social connections. RDS is invaluable to the study of hard-to-reach populations. However, RDS is costly and can be infeasible. RDS is infeasible when RDS point estimators have small effective sample sizes (large design effects) or when RDS interval estimators have large confidence intervals relative to estimates obtained in previous studies or poor coverage. As a result, researchers need tools to a...
• DISENTANGLING AND ASSESSING UNCERTAINTIES IN MULTIPERIOD CORPORATE DEFAULT RISK PREDICTIONS AI翻译
  作者：Yuan, Mia; Tang, Cheng Yong; Hong, Yili; Yang, Jian
  作者单位：Virginia Polytechnic Institute & State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; University of Colorado System; University of Colorado Denver
  摘要：Measuring the corporate default risk is broadly important in economics and finance. Quantitative methods have been developed to predictively assess future corporate default probabilities. However, as a more difficult yet crucial problem, evaluating the uncertainties associated with the default predictions remains little explored. In this paper, we attempt to fill this blank by developing a procedure for quantifying the level of associated uncertainties upon carefully disentangling multiple con...
• JOINT SIGNIFICANCE TESTS FOR MEDIATION EFFECTS OF SOCIOECONOMIC ADVERSITY ON ADIPOSITY VIA EPIGENETICS AI翻译
  作者：Huang, Yen-Tsung
  作者单位：Academia Sinica - Taiwan
  摘要：Mediation analysis has become a popular practice in biomedical research. We conduct mediation analyses to investigate whether epigenetic variations mediate the effect of socioeconomic disadvantage on adiposity. Mediation effects can be expressed as a product of two parameters: one for the exposure-mediator association and the other for the mediator-outcome association conditional on the exposure. Under multi-mediator models, we study joint significance tests which examine the two parameters se...
• SIMULTANEOUS MODELLING OF MOVEMENT, MEASUREMENT ERROR, AND OBSERVER DEPENDENCE IN MARK-RECAPTURE DISTANCE SAMPLING: AN APPLICATION TO ARCTIC BIRD SURVEYS AI翻译
  作者：Conn, Paul B.; Alisauskas, Ray T.
  作者单位：National Oceanic Atmospheric Admin (NOAA) - USA; Environment & Climate Change Canada; Canadian Wildlife Service; Wildlife Research Division - Environment Canada
  摘要：Mark-recapture distance sampling is a promising method for surveying bird populations from aircraft in open landscapes. However, commonly available distance sampling estimators require that distances to target animals are made without error and that animals are stationary while sampling is being conducted. Motivated by a recent bird survey where these requirements were routinely violated, we describe a marginal likelihood framework for estimating abundance from double-observer data that can ac...
• REDUCING STORAGE OF GLOBAL WIND ENSEMBLES WITH STOCHASTIC GENERATORS AI翻译
  作者：Jeong, Jaehong; Castruccio, Stefano; Crippa, Paola; Genton, Marc G.
  作者单位：King Abdullah University of Science & Technology; University of Notre Dame; University of Notre Dame
  摘要：Wind has the potential to make a significant contribution to future energy resources. Locating the sources of this renewable energy on a global scale is however extremely challenging, given the difficulty to store very large data sets generated by modern computer models. We propose a statistical model that aims at reproducing the data-generating mechanism of an ensemble of runs via a Stochastic Generator (SG) of global annual wind data. We introduce an evolutionary spectrum approach with spati...
• ePCA: HIGH DIMENSIONAL EXPONENTIAL FAMILY PCA AI翻译
  作者：Liu, Lydia T.; Dobriban, Edgar; Singer, Amit
  作者单位：University of California System; University of California Berkeley; University of Pennsylvania; Princeton University; Princeton University
  摘要：Many applications involve large datasets with entries from exponential family distributions. Our main motivating application is photon-limited imaging, where we observe images with Poisson distributed pixels. We focus on X-ray Free Electron Lasers (XFEL), a quickly developing technology whose goal is to reconstruct molecular structure. In XFEL, estimating the principal components of the noiseless distribution is needed for denoising and for structure determination. However, the standard method...
• SCALPEL: EXTRACTING NEURONS FROM CALCIUM IMAGING DATA AI翻译
  作者：Petersen, Ashley; Simon, Noah; Witten, Daniela
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
  摘要：In the past few years, new technologies in the field of neuroscience have made it possible to simultaneously image activity in large populations of neurons at cellular resolution in behaving animals. In mid-2016, a huge repository of this so-called calcium imaging data was made publicly available. The availability of this large-scale data resource opens the door to a host of scientific questions for which new statistical methods must be developed. In this paper we consider the first step in th...
• TREE-BASED REINFORCEMENT LEARNING FOR ESTIMATING OPTIMAL DYNAMIC TREATMENT REGIMES AI翻译
  作者：Tao, Yebin; Wang, Lu; Almirall, Daniel
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Dynamic treatment regimes (DTRs) are sequences of treatment decision rules, in which treatment may be adapted over time in response to the changing course of an individual. Motivated by the substance use disorder (SUD) study, we propose a tree-based reinforcement learning (T-RL) method to directly estimate optimal DTRs in a multi-stage multi-treatment setting. At each stage, T-RL builds an unsupervised decision tree that directly handles the problem of optimization with multiple treatment comp...
• NONPARAMETRIC BAYESIAN LEARNING OF HETEROGENEOUS DYNAMIC TRANSCRIPTION FACTOR NETWORKS AI翻译
  作者：Luo, Xiangyu; Wei, Yingying
  作者单位：Chinese University of Hong Kong; Chinese University of Hong Kong
  摘要：Gene expression is largely controlled by transcription factors (TFs) in a collaborative manner. Therefore, an understanding of TF collaboration is crucial for the elucidation of gene regulation. The co-activation of TFs can be represented by networks. These networks are dynamic in diverse biological conditions and heterogeneous across the genome within each biological condition. Existing methods for construction of TF networks lack solid statistical models, analyze each biological condition se...
• DISCOVERING POLITICAL TOPICS IN FACEBOOK DISCUSSION THREADS WITH GRAPH CONTEXTUALIZATION AI翻译
  作者：Zhang, Yilin; Poux-Berthe, Marie; Wells, Chris; Koc-Michalska, Karolina; Rohe, Karl
  作者单位：University of Wisconsin System; University of Wisconsin Madison; Audencia; Boston University
  摘要：We propose a graph contextualization method, pairGraphText, to study political engagement on Facebook during the 2012 French presidential election. It is a spectral algorithm that contextualizes graph data with text data for online discussion thread. In particular, we examine the Facebook posts of the eight leading candidates and the comments beneath these posts. We find evidence of both (i) candidate-centered structure, where citizens primarily comment on the wall of one candidate and (ii) is...