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作者：Wang, Yan; Yue, Xiaowei; Tuo, Rui; Hunt, Jeffrey H.; Shi, Jianjun
作者单位：Beijing University of Technology; Virginia Polytechnic Institute & State University; Texas A&M University System; Texas A&M University College Station; Boeing; University System of Georgia; Georgia Institute of Technology
摘要：Estimation of model parameters of computer simulators, also known as calibration, is an important topic in many engineering applications. In this paper we consider the calibration of computer model parameters with the help of engineering design knowledge. We introduce the concept of sensible (calibration) variables. Sensible variables are model parameters, which are sensitive in the engineering modeling, and whose optimal values differ from the engineering design values. We propose an effectiv...
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作者：Sandholtz, Nathan; Bornn, Luke
作者单位：Simon Fraser University
摘要：In this paper we model basketball plays as episodes from team-specific nonstationary Markov decision processes (MDPs) with shot clock dependent transition probabilities. Bayesian hierarchical models are employed in the modeling and parametrization of the transition probabilities to borrow strength across players and through time. To enable computational feasibility, we combine lineup-specific MDPs into team-average MDPs using a novel transition weighting scheme. Specifically, we derive the dyn...
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作者：Touloupou, Panayiota; Finkenstadt, Barbel; Besser, Thomas E.; French, Nigel P.; Spencer, Simon E. F.
作者单位：University of Warwick; Washington State University
摘要：For most pathogens, testing procedures can be used to distinguish between different strains with which individuals are infected. Due to the growing availability of such data, multistrain models have increased in popularity over the past few years. Quantifying the interactions between different strains of a pathogen is crucial in order to obtain a more complete understanding of the transmission process, but statistical methods for this type of problem are still in the early stages of developmen...
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作者：Baker, Yulia; Tang, Tiffany M.; Allen, Genevera, I
作者单位：Rice University; University of California System; University of California Berkeley; Rice University
摘要：Data integration methods that analyze multiple sources of data simultaneously can often provide more holistic insights than can separate inquiries of each data source. Motivated by the advantages of data integration in the era of big data, we investigate feature selection for high-dimensional multiview data with mixed data types (e.g., continuous, binary, count-valued). This heterogeneity of multiview data poses numerous challenges for existing feature selection methods. However, after critica...
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作者：Liu, Yusha; Li, Meng; Morris, Jeffrey S.
作者单位：Rice University; University of Pennsylvania
摘要：Mass spectrometry proteomics, characterized by spiky, spatially heterogeneous functional data, can be used to identify potential cancer biomarkers. Existing mass spectrometry analyses utilize mean regression to detect spectral regions that are differentially expressed across groups. However, given the interpatient heterogeneity that is a key hallmark of cancer, many biomarkers are only present at aberrant levels for a subset of, not all, cancer samples. Differences in these biomarkers can easi...
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作者：Koslovsky, Matthew D.; Hebert, Emily T.; Businelle, Michael S.; Vannucci, Marina
作者单位：Colorado State University System; Colorado State University Fort Collins; University of Oklahoma System; University of Oklahoma - Norman; University of Oklahoma Health Sciences Center; Rice University
摘要：The integration of mobile health (mHealth) devices into behavioral health research has fundamentally changed the way researchers and interventionalists are able to collect data as well as deploy and evaluate intervention strategies. In these studies, researchers often collect intensive longitudinal data (ILD) using ecological momentary assessment methods which aim to capture psychological, emotional and environmental factors that may relate to a behavioral outcome in near real time. In order t...
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作者：Papadogeorgou, Georgia; Dominici, Francesca
作者单位：Duke University; Harvard University; Harvard T.H. Chan School of Public Health
摘要：In the last two decades ambient levels of air pollution have declined substantially. At the same time the Clean Air Act mandates that the National Ambient Air Quality Standards (NAAQS) must be routinely assessed to protect populations based on the latest science. Therefore, researchers should continue to address the following question: is exposure to levels of air pollution below the NAAQS harmful to human health? Furthermore, the contentious nature surrounding environmental regulations urges ...
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作者：Zhou, Tianjian; Sengupta, Subhajit; Muller, Peter; Ji, Yuan
作者单位：University of Chicago; NorthShore University Health System; University of Texas System; University of Texas Austin
摘要：Tumor cell population consists of genetically heterogeneous subpopulations, known as subclones. Bulk sequencing data using high-throughput sequencing technology provide total and variant DNA and RNA read counts for many nucleotide loci as a mixture of signals from different subclones. We present RNDClone as a tool to deconvolute the mixture and reconstruct the subclones with distinct DNA genotypes and RNA expression profiles. In particular, we infer the number and population frequencies of sub...
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作者：Brantley, Halley L.; Guinness, Joseph; Chi, Eric C.
作者单位：North Carolina State University; Cornell University
摘要：We address the problem of estimating smoothly varying baseline trends in time series data. This problem arises in a wide range of fields, including chemistry, macroeconomics and medicine; however, our study is motivated by the analysis of data from low cost air quality sensors. Our methods extend the quantile trend filtering framework to enable the estimation of multiple quantile trends simultaneously while ensuring that the quantiles do not cross. To handle the computational challenge posed b...
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作者：Fisher, Jared D.; Pettenuzzo, Davide; Carvalho, Carlos M.
作者单位：University of California System; University of California Berkeley; Brandeis University; University of Texas System; University of Texas Austin
摘要：We introduce a fast, closed-form, simulation-free method to model and forecast multiple asset returns and employ it to investigate the optimal ensemble of features to include when jointly predicting monthly stock and bond excess returns. Our approach builds on the Bayesian dynamic linear models of West and Harrison (Bayesian Forecasting and Dynamic Models (1997) Springer), and it can objectively determine, through a fully automated procedure, both the optimal set of regressors to include in th...
