The Annals of Applied Statistics

最新文章

• HIERARCHICAL RESAMPLING FOR BAGGING IN MULTISTUDY PREDICTION WITH APPLICATIONS TO HUMAN NEUROCHEMICAL SENSING AI翻译
  作者：Loewinger, Gabriel; Patil, Prasad; Kishida, Kenneth T.; Parmigiani, Giovanni
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Boston University; Wake Forest University; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
  摘要：We propose the study strap ensemble, which combines advantages of two common approaches to fitting prediction models when multiple training datasets (studies) are available: pooling studies and fitting one model vs. averaging predictions from multiple models each fit to individual studies. The study strap ensemble fits models to bootstrapped datasets or pseudo-studies. These are generated by resampling from multiple studies with a hierarchical resampling scheme that generalizes the randomized ...
• MAPPING INTERSTELLAR DUST WITH GAUSSIAN PROCESSES AI翻译
  作者：Miller, Andrew C.; Anderson, Lauren; Leistedt, Boris; Cunningham, John P.; Hogg, David W.; Blei, David M.
  作者单位：Columbia University; Columbia University; New York University; Simons Foundation; Flatiron Institute
  摘要：Interstellar dust corrupts nearly every stellar observation and accounting for it is crucial to measuring physical properties of stars. We model the dust distribution as a spatially varying latent field with a Gaussian process (GP) and develop a likelihood model and inference method that scales to millions of astronomical observations. Modeling interstellar dust is complicated by two factors. The first is integrated observations. The data come from a van-tage point on Earth, and each observati...
• FULL BAYESIAN INFERENCE IN HIDDEN MARKOV MODELS OF PLANT GROWTH AI翻译
  作者：Viaud, Gautier; Chen, Yuting; Cournede, Paul-Henry
  作者单位：Universite Paris Saclay; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory
  摘要：Accurately modeling the growth process of plants in interaction with their environment is important for predicting their biophysical characteris-tics, referred to as phenotype prediction. Most models are described by dis-crete dynamic systems in general state-space representation with important domain-specific characteristics: First, plant model parameters have usually clear functional meanings and may be of genetic origins, thus necessitating a precise estimation. Second, critical growth vari...
• SPATIOTEMPORAL SATELLITE DATA IMPUTATION USING SPARSE FUNCTIONAL DATA ANALYSIS AI翻译
  作者：Zhu, Weicheng; Zhu, Zhengyuan; Dai, Xiangtao
  作者单位：Iowa State University
  摘要：Many scientific applications and signal processing algorithms require complete satellite images. However, missing data in satellite images is very common due to various reasons such as cloud cover and sensor-specific prob-lems. This paper introduces a general spatiotemporal satellite image impu-tation method based on sparse functional data analytic techniques. To han-dle observations consisting of a few longitudinally repeated satellite images that are themselves partially observed and noise-c...
• SEMIPARAMETRIC POINT PROCESS MODELING OF BLINKING ARTIFACTS IN PALM AI翻译
  作者：Jensen, Louis G.; Williamson, David J.; Hahn, Ute
  作者单位：Aarhus University; University of London; King's College London
  摘要：Photoactivated localization microscopy (PALM) is a powerful imaging technique for characterization of protein organization in biological cells. Due to the stochastic blinking of fluorescent probes and camera discretization effects, each protein gives rise to a cluster of artificial observations. These blinking artifacts are an obstacle for quantitative analysis of PALM data, and tools for their correction are in high demand. We develop the independent blinking cluster point process (IBCpp) fam...
• MEASUREMENT ERROR CORRECTION IN PARTICLE TRACKING MICRORHEOLOGY AI翻译
  作者：Ling, Yun; Lysy, Martin; Seim, Ian; Newby, Jay; Hill, David B.; Cribb, Jeremy; Forest, M. Gregory
  作者单位：University of Waterloo; University of North Carolina; University of North Carolina Chapel Hill; University of Alberta; 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：In diverse biological applications, single-particle tracking (SPT) of passive microscopic species has become the experimental measurement of choice, when either the materials are of limited volume or so soft as to deform uncontrollably when manipulated by traditional instruments. In a wide range of SPT experiments, a ubiquitous finding is that of long-range dependence in the particles' motion. This is characterized by a power-law signature in the mean squared displacement (MSD) of particle pos...
• MODEL-BASED DISTANCE EMBEDDING WITH APPLICATIONS TO CHROMOSOMAL CONFORMATION BIOLOGY AI翻译
  作者：Zhang, Yuping; Mao, Disheng; Ouyang, Zhengqing
  作者单位：University of Connecticut; University of Massachusetts System; University of Massachusetts Amherst
  摘要：Recent development of high-throughput biotechnologies, such as Hi-C, have enabled genome-wide measurement of chromosomal conformation. The interaction signals among genomic loci are contaminated with noises. It remains largely unknown how well the underlying chromosomal conformation can be elucidated, based on massive and noisy measurements. We propose a new model-based distance embedding (MDE) framework, to reveal spatial organizations of chromosomes. The proposed framework is a general metho...
• MEASURING PERFORMANCE FOR END-OF-LIFE CARE AI翻译
  作者：Haneuse, Sebastien; Schrag, Deborah; Dominici, Francesca; Normand, Sharon-Lise; Lee, Kyu Ha
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard Medical School
  摘要：Although not without controversy, readmission is entrenched as a hospital quality metric with statistical analyses generally based on fitting a logistic-Normal generalized linear mixed model. Such analyses, however, ignore death as a competing risk, although doing so for clinical conditions with high mortality can have profound effects; a hospital's seemingly good performance for readmission may be an artifact of it having poor performance for mortality. In this paper we propose novel multivar...
• INFERENCE IN BAYESIAN ADDITIVE VECTOR AUTOREGRESSIVE TREE MODELS AI翻译
  作者：Huber, Florian; Rossini, Luca
  作者单位：Salzburg University; University of Milan
  摘要：Vector autoregressive (VAR) models assume linearity between the endogenous variables and their lags. This assumption might be overly restrictive and could have a deleterious impact on forecasting accuracy. As a solution we propose combining VAR with Bayesian additive regression tree (BART) models. The resulting Bayesian additive vector autoregressive tree (BAVART) model is capable of capturing arbitrary nonlinear relations between the endogenous variables and the covariates without much input ...
• CAUSAL INFERENCE FOR THE EFFECT OF MOBILITY ON COVID-19 DEATHS AI翻译
  作者：Bonvini, Matteo; Kennedy, Edward H.; Ventura, Valerie; Wasserman, Larry
  作者单位：Carnegie Mellon University
  摘要：In this paper we develop statistical methods for causal inference in epi-demics. Our focus is in estimating the effect of social mobility on deaths in the first year of the Covid-19 pandemic. We propose a marginal structural model motivated by a basic epidemic model. We estimate the counterfactual time series of deaths under interventions on mobility. We conduct several types of sensitivity analyses. We find that the data support the idea that reduced mo-bility causes reduced deaths, but the c...