منابع مشابه
High-Dimensional Bayesian Geostatistics.
With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understan...
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An understanding of the Earth’s climate system benefits all sectors of the economy and environment. Several challenges faced when modeling the Earth’s climate system include: estimating geographical features of global datasets, making inferences from multiple data-products, and providing diagnostic tools for complex Earth models. Existing geostatistical approaches address these challenges by mo...
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Biography Dr. Dan Cornford is a lecture in Computer Science and works in the Neural Computing Research Group at Aston University. Research interests are in the field of spatial statistics, space-time modelling and data assimilation. Lehel Csato is a post-doc in the same group working on an EPSRC grant (GR/R61857/01) looking at applying sparse sequential Gaussian processes to data assimilation. ...
متن کاملBayesian Nonparametric Methods for High-dimensional Data
DAVID C. KESSLER: Bayesian Nonparametric Methods for High-Dimensional Data (Under the direction of Dr. David B. Dunson and Dr. Amy H. Herring) Bayesian nonparametric (BNP or NP Bayes) methods have enjoyed great strides forward in recent years. BNP methods embody the belief that inference is best driven by the data itself with minimal assumptions about the underlying model; this approach has mot...
متن کاملBayesian Model Selection in High-Dimensional Settings.
Standard assumptions incorporated into Bayesian model selection procedures result in procedures that are not competitive with commonly used penalized likelihood methods. We propose modifications of these methods by imposing nonlocal prior densities on model parameters. We show that the resulting model selection procedures are consistent in linear model settings when the number of possible covar...
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ژورنال
عنوان ژورنال: Bayesian Analysis
سال: 2017
ISSN: 1936-0975
DOI: 10.1214/17-ba1056r