The Annals of Applied Statistics

最新文章

• ACCOUNTING FOR DROP-OUT USING INVERSE PROBABILITY CENSORING WEIGHTS IN LONGITUDINAL CLUSTERED DATA WITH INFORMATIVE CLUSTER SIZE AI翻译
  作者：Mitani, Aya A.; Kaye, Elizabeth K.; Nelson, Kerrie P.
  作者单位：University of Toronto; Boston University; Boston University
  摘要：Periodontal disease is a serious gum infection impacting half of the U.S. adult population that may lead to loss of teeth. Using standard marginal models to study the association between patient-level predictors and tooth-level outcomes can lead to biased estimates because the independence assumption between the outcome (periodontal disease) and cluster size (number of teeth per patient) is violated. Specifically, the baseline number of teeth of a patient is informative. In this setting a clus...
• HOW MANY REFUGEES AND MIGRANTS DIED TRYING TO REACH EUROPE? JOINT POPULATION SIZE AND TOTAL ESTIMATION AI翻译
  作者：Farcomeni, Alession
  作者单位：University of Rome Tor Vergata
  摘要：We estimate the number of migrants and refugees that died while trying to enter the European Union, during a period of 25 years. Only a subset of at-tempts with at least one casualty are reported by at least one media source. In order to obtain the estimate, we propose a regression-extrapolation approach, for joint estimation of population size (here, the number of deadly individual or group attempts) and the sum of an accompanying trait (here, the number of deaths) over the population. The tr...
• B-SCALING: A NOVEL NONPARAMETRIC DATA FUSION METHOD AI翻译
  作者：Liu, Yiwen; Sun, Xiaoxiao; Zhong, Wenxuan; Li, Bing
  作者单位：University of Arizona; University System of Georgia; University of Georgia; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Very often for the same scientific question, there may exist different techniques or experiments that measure the same numerical quantity. Historically, various methods have been developed to exploit the information within each type of data independently. However, statistical data fusion methods that could effectively integrate multisource data under a unified framework are lacking. In this paper we propose a novel data fusion method, called Bscaling, for integrating multisource data. Consider...
• BIDIMENSIONAL LINKED MATRIX FACTORIZATION FOR PAN-OMICS PAN-CANCER ANALYSIS AI翻译
  作者：Lock, Eric F.; Park, Jun Young; Hoadley, Katherine A.
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Toronto; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Several modern applications require the integration of multiple large data matrices that have shared rows and/or columns. For example, cancer studies that integrate multiple omics platforms across multiple types of cancer, pan-omics pan-cancer analysis, have extended our knowledge of molecular heterogeneity beyond what was observed in single tumor and single platform studies. However, these studies have been limited by available statistical methodology. We propose a flexible approach to the si...
• HIERARCHICAL BAYESIAN MODELING OF OCEAN HEAT CONTENT AND ITS UNCERTAINTY AI翻译
  作者：Baugh, Samuel; Mckinnon, Karen
  作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
  摘要：The accurate quantification of changes in the heat content of the world's oceans is crucial for our understanding of the effects of increasing green-house gas concentrations. The Argo program, consisting of Lagrangian floats that measure vertical temperature profiles throughout the global ocean, has provided a wealth of data from which to estimate ocean heat content. How-ever, creating a globally consistent statistical model for ocean heat content remains challenging due to the need for a glob...
• EXTENDED STOCHASTIC BLOCK MODELS WITH APPLICATION TO CRIMINAL NETWORKS AI翻译
  作者：Legramanti, Sirio; Rigon, Tommaso; Durante, Daniele; Dunson, David B.
  作者单位：Bocconi University; Bocconi University; University of Milano-Bicocca; Duke University
  摘要：Reliably learning group structures among nodes in network data is challenging in several applications. We are particularly motivated by studying covert networks that encode relationships among criminals. These data are subject to measurement errors, and exhibit a complex combination of an unknown number of core-periphery, assortative and disassortative structures that may unveil key architectures of the criminal organization. The coexistence of these noisy block patterns limits the reliability...
• GRAPH LINK PREDICTION IN COMPUTER NETWORKS USING POISSON MATRIX FACTORISATION AI翻译
  作者：Passino, Francesco Sanna; Turcotte, Melissa J. M.; Heard, Nicholas A.
  作者单位：Imperial College London; Microsoft
  摘要：Graph link prediction is an important task in cybersecurity: relationships between entities within a computer network, such as users interacting with computers or system libraries and the corresponding processes that use them, can provide key insights into adversary behaviour. Poisson matrix factorisation (PMF) is a popular model for link prediction in large networks, particularly useful for its scalability. In this article PMF is extended to include scenarios that are commonly encountered in ...
• BAYESIAN INVERSE REINFORCEMENT LEARNING FOR COLLECTIVE ANIMAL MOVEMENT AI翻译
  作者：Schafer, Toryn L. J.; Wikle, Christopher K.; Hooten, Mevin B.
  作者单位：University of Missouri System; University of Missouri Columbia; United States Department of the Interior; United States Geological Survey; Colorado State University System; Colorado State University Fort Collins; Colorado State University System; Colorado State University Fort Collins; Colorado State University System; Colorado State University Fort Collins
  摘要：Agent-based methods allow for defining simple rules that generate complex group behaviors. The governing rules of such models are typically set a priori, and parameters are tuned from observed behavior trajectories. Instead of making simplifying assumptions across all anticipated scenarios, inverse reinforcement learning provides inference on the short-term (local) rules governing long-term behavior policies by using properties of a Markov decision process. We use the computationally efficient...
• MARKOV-MODULATED HAWKES PROCESSES FOR MODELING SPORADIC AND BURSTY EVENT OCCURRENCES IN SOCIAL INTERACTIONS AI翻译
  作者：Wu, Jing; Ward, Owen G.; Curley, James; Zheng, Tian
  作者单位：Columbia University; University of Texas System; University of Texas Austin
  摘要：Modeling event dynamics is central to many disciplines. Patterns in observed social interaction events can be commonly modeled using point processes. Such social interaction event data often exhibit self-exciting, heterogeneous and sporadic trends which is challenging for conventional models. It is reasonable to assume that there exists a hidden state process that drives different event dynamics at different states. In this paper we propose a Markov modulated Hawkes process (MMHP) model for le...
• BATCH-SEQUENTIAL DESIGN AND HETEROSKEDASTIC SURROGATE MODELING FOR DELTA SMELT CONSERVATION AI翻译
  作者：Zhang, Boya; Gramacy, Robert B.; Johnson, Leah R.; Rose, Kenneth A.; Smith, Eric
  作者单位：Virginia Polytechnic Institute & State University; University System of Maryland; University of Maryland Center for Environmental Science
  摘要：Delta smelt is an endangered fish species in the San Francisco estuary that have shown an overall population decline over the past 30 years. Researchers have developed a stochastic, agent-based simulator to virtualize the system with the goal of understanding the relative contribution of natural and anthropogenic factors that might play a role in their decline. However, the input configuration space is high dimensional, running the simulator is time-consuming, and its noisy outputs change nonl...