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作者：Afsari, Bahman; Braga-Neto, Ulisses M.; Geman, Donald
作者单位：Johns Hopkins University; Texas A&M University System; Texas A&M University College Station; Johns Hopkins University
摘要：Statistical methods for analyzing large-scale biomolecular data are commonplace in computational biology. A notable example is phenotype prediction from gene expression data, for instance, detecting human cancers, differentiating subtypes and predicting clinical outcomes. Still, clinical applications remain scarce. One reason is that the complexity of the decision rules that emerge from standard statistical learning impedes biological understanding, in particular, any mechanistic interpretatio...
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作者：Kumazawa, Takao; Ogata, Yosihiko
作者单位：Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan; University of Tokyo
摘要：The conditional intensity function of a point process is a useful tool for generating probability forecasts of earthquakes. The epidemic-type aftershock sequence (ETAS) model is defined by a conditional intensity function, and the corresponding point process is equivalent to a branching process, assuming that an earthquake generates a cluster of offspring earthquakes (triggered earthquakes or so-called aftershocks). Further, the size of the first-generation cluster depends on the magnitude of ...
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作者：Meyer, Sebastian; Held, Leonhard
作者单位：University of Zurich; Swiss School of Public Health (SSPH+)
摘要：Short-time human travel behaviour can be described by a power law with respect to distance. We incorporate this information in space-time models for infectious disease surveillance data to better capture the dynamics of disease spread. Two previously established model classes are extended, which both decompose disease risk additively into endemic and epidemic components: a spatio-temporal point process model for individual-level data and a multivariate time-series model for aggregated count da...
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作者：Wilson, James D.; Wang, Simi; Mucha, Peter J.; Bhamidi, Shankar; Nobel, Andrew B.
作者单位：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：A common and important problem arising in the study of networks is how to divide the vertices of a given network into one or more groups, called communities, in such a way that vertices of the same community are more interconnected than vertices belonging to different ones. We propose and investigate a testing based community detection procedure called Extraction of Statistically Significant Communities (ESSC). The ESSC procedure is based on p-values for the strength of connection between a si...
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作者：Cervone, Daniel; Pillai, Natesh S.; Pati, Debdeep; Berbeco, Ross; Lewis, John Henry
作者单位：Harvard University; State University System of Florida; Florida State University; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Brigham & Women's Hospital; Harvard University; Harvard Medical School
摘要：Lung tumor tracking for radiotherapy requires real-time, multiple-step ahead forecasting of a quasi-periodic time series recording instantaneous tumor locations. We introduce a location-mixture autoregressive (LMAR) process that admits multimodal conditional distributions, fast approximate inference using the EM algorithm and accurate multiple-step ahead predictive distributions. LMAR outperforms several commonly used methods in terms of out-of-sample prediction accuracy using clinical data fr...
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作者：Bleich, Justin; Kapelner, Adam; George, Edward I.; Jensen, Shane T.
作者单位：University of Pennsylvania
摘要：We consider the task of discovering gene regulatory networks, which are defined as sets of genes and the corresponding transcription factors which regulate their expression levels. This can be viewed as a variable selection problem, potentially with high dimensionality. Variable selection is especially challenging in high-dimensional settings, where it is difficult to detect subtle individual effects and interactions between predictors. Bayesian Additive Regression Trees [BART, Ann. Appl. Stat...
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作者：Zhou, Rensheng; Serban, Nicoleta; Gebraeel, Nagi
作者单位：University System of Georgia; Georgia Institute of Technology
摘要：Degradation modeling has traditionally relied on historical signals to estimate the behavior of the underlying degradation process. Many models assume that these historical signals are acquired under the same environmental conditions and can be observed along the entire lifespan of a component. In this paper, we relax these assumptions and present a more general statistical framework for modeling degradation signals that may have been collected under different types of environmental conditions...
