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作者：Chatterjee, Snigdhansu; Qiu, Peihua
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：This paper deals with phase II, univariate, statistical process control when a set of in-control data is available, and when both the in-control and out-of-control distributions of the process are unknown. Existing process control techniques typically require substantial knowledge about the in-control and out-of-control distributions of the process, which is often difficult to obtain in practice. We propose (a) using a sequence of control limits for the cumulative sum (CUSUM) control charts, w...
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作者：Culp, Mark; Michailidis, George; Johnson, Kjell
作者单位：West Virginia University; University of Michigan System; University of Michigan; Pfizer; Pfizer USA
摘要：In many scientific settings data can be naturally partitioned into variable groupings called views. Common examples include environmental (1st view) and genetic information (2nd view) in ecological applications, chemical (1st view) and biological (2nd view) data in drug discovery. Multi-view data also occur in text analysis and proteomics applications where one view consists of a graph with observations as the vertices and a weighted measure of pairwise similarity between observations as the e...
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作者：Mandal, Abhyuday; Ranjan, Pritam; Wu, C. F. Jeff
作者单位：University System of Georgia; University of Georgia; Acadia University; University System of Georgia; Georgia Institute of Technology
摘要：Identifying promising compounds from a vast collection of feasible compounds is an important and yet challenging problem in the pharmaceutical industry. An efficient solution to this problem will help reduce the expenditure at the early stages of drug discovery. In an attempt to solve this problem, Mandal, Wu and Johnson [Technometrics 48 (2006) 273-283] proposed the SELC algorithm. Although powerful, it fails to extract substantial information from the data to guide the search efficiently, as...
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作者：Breto, Carles; He, Daihai; Ionides, Edward L.; King, Aaron A.
作者单位：Universidad Carlos III de Madrid; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：The purpose of time series analysis via mechanistic models is to reconcile the known or hypothesized structure of a dynamical system with observations collected over time. We develop a framework for Constructing nonlinear mechanistic models and carrying Out inference. Our framework permits the consideration of implicit dynamic models, meaning statistical models for stochastic dynamical systems which are specified by a simulation algorithm to generate sample paths. Inference procedures that ope...
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作者：Paciorek, Christopher J.; Yanosky, Jeff D.; Puett, Robin C.; Laden, Francine; Suh, Helen H.
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard T.H. Chan School of Public Health; University of South Carolina System; University of South Carolina Columbia; University of South Carolina System; University of South Carolina Columbia; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital; Harvard University; Harvard Medical School; Harvard University; Harvard T.H. Chan School of Public Health
摘要：The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. W...
