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作者：Guinness, Joseph; Stein, Michael L.
作者单位：University of Chicago; University of Chicago
摘要：The Atmospheric Radiation Measurement program is a U.S. Department of Energy project that collects meteorological observations at several locations around the world in order to study how weather processes affect global climate change. As one of its initiatives, it operates a set of fixed but irregularly-spaced monitoring facilities in the Southern Great Plains region of the U. S. We describe methods for interpolating temperature records from these fixed facilities to locations at which no obse...
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作者：Alfons, Andreas; Croux, Christophe; Gelper, Sarah
作者单位：KU Leuven; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC
摘要：Sparse model estimation is a topic of high importance in modern data analysis due to the increasing availability of data sets with a large number of variables. Another common problem in applied statistics is the presence of outliers in the data. This paper combines robust regression and sparse model estimation. A robust and sparse estimator is introduced by adding an L-1 penalty on the coefficient estimates to the well-known least trimmed squares (LTS) estimator. The breakdown point of this sp...
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作者：Lee, Giwhyun; Byon, Eunshin; Ntaimo, Lewis; Ding, Yu
作者单位：Texas A&M University System; Texas A&M University College Station; University of Michigan System; University of Michigan
摘要：This study presents a Bayesian parametric model for the purpose of estimating the extreme load on a wind turbine. The extreme load is the highest stress level imposed on a turbine structure that the turbine would experience during its service lifetime. A wind turbine should be designed to resist such a high load to avoid catastrophic structural failures. To assess the extreme load, turbine structural responses are evaluated by conducting field measurement campaigns or performing aeroelastic si...
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作者：Savitsky, Terrance D.; Paddock, Susan M.
作者单位：RAND Corporation
摘要：We develop a dependent Dirichlet process (DDP) model for repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each client through a sequence of elements which overlap with those of other clients on different occasions. Our interest concentrates on study designs for which the overlaps of sequences occur for clients who receive an intervention in a shared or grouped fashion whose memberships may change over multiple tr...
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作者：Meister, Arwen; Li, Ye Henry; Choi, Bokyung; Wong, Wing Hung
作者单位：Stanford University
摘要：Biological structure and function depend on complex regulatory interactions between many genes. A wealth of gene expression data is available from high-throughput genome-wide measurement technologies, but effective gene regulatory network inference methods are still needed. Model-based methods founded on quantitative descriptions of gene regulation are among the most promising, but many such methods rely on simple, local models or on ad hoc inference approaches lacking experimental interpretab...
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作者：Vu, Duy Q.; Hunter, David R.; Schweinberger, Michael
作者单位：University of Melbourne; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Rice University
摘要：We describe a network clustering framework, based on finite mixture models, that can be applied to discrete-valued networks with hundreds of thousands of nodes and billions of edge variables. Relative to other recent model-based clustering work for networks, we introduce a more flexible modeling framework, improve the variational-approximation estimation algorithm, discuss and implement standard error estimation via a parametric bootstrap approach, and apply these methods to much larger data s...
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作者：Kleiber, William; Katz, Richard W.; Rajagopalan, Balaji
作者单位：University of Colorado System; University of Colorado Boulder; National Center Atmospheric Research (NCAR) - USA; University of Colorado System; University of Colorado Boulder
摘要：Spatiotemporal simulation of minimum and maximum temperature is a fundamental requirement for climate impact studies and hydrological or agricultural models. Particularly over regions with variable orography, these simulations are difficult to produce due to terrain driven nonstationarity. We develop a bivariate stochastic model for the spatiotemporal field of minimum and maximum temperature. The proposed framework splits the bivariate field into two components of local climate and weather. Th...
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作者：Jiang, Xun; Dey, Dipak K.; Prunier, Rachel; Wilson, Adam M.; Holsinger, Kent E.
作者单位：University of Connecticut; Yale University; Connecticut State University System; Western Connecticut State University; University of Connecticut
摘要：Understanding the mechanisms that allow biological species to co-occur is of great interest to ecologists. Here we investigate the factors that influence co-occurrence of members of the genus Protea in the Cape Floristic Region of southwestern Africa, a global hot spot of biodiversity. Due to the binomial nature of our response, a critical issue is to choose appropriate link functions for the regression model. In this paper we propose a new family of flexible link functions for modeling binomi...
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作者：Imai, Kosuke; Ratkovic, Marc
作者单位：Princeton University
摘要：When evaluating the efficacy of social programs and medical treatments using randomized experiments, the estimated overall average causal effect alone is often of limited value and the researchers must investigate when the treatments do and do not work. Indeed, the estimation of treatment effect heterogeneity plays an essential role in (1) selecting the most effective treatment from a large number of available treatments, (2) ascertaining subpopulations for which a treatment is effective or ha...
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作者：Fu, Audrey Qiuyan; Russell, Steven; Bray, Sarah J.; Tavare, Simon
作者单位：University of Cambridge; University of Cambridge; University of Cambridge; University of Southern California
摘要：To identify novel dynamic patterns of gene expression, we develop a statistical method to cluster noisy measurements of gene expression collected from multiple replicates at multiple time points, with an unknown number of clusters. We propose a random-effects mixture model coupled with a Dirichlet-process prior for clustering. The mixture model formulation allows for probabilistic cluster assignments. The random-effects formulation allows for attributing the total variability in the data to th...
