Abstract Details
Activity Number:
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97
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Type:
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Roundtables
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Date/Time:
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Monday, August 5, 2013 : 7:00 AM to 8:15 AM
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Sponsor:
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Section on Statistics and the Environment
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Abstract - #307542 |
Title:
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Statistics for Spatio-Temporal Data: New Challenges
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Author(s):
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Christopher K. Wikle*+
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Companies:
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University of Missouri
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Keywords:
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big data ;
nonlinear ;
spatial ;
hierarchical ;
environmental
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Abstract:
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From understanding environmental processes and climate trends to developing new technologies for mapping public health data and the spread of invasive species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. The recently published book by Cressie and Wikle, "Statistics for Spatio-Temporal Data" (2011) , presents a systematic approach to quantitative techniques for the statistical analysis of such data. These methods feature statistical modeling with an emphasis on dynamical spatio-temporal models. Discussion will build on these ideas and focus on the utility of these methods with an emphasis on new challenges in spatio-temporal modeling. Some of these challenges include dimensionality, computation, incorporation of "big data," nonlinearity, and realistic measurement and sampling uncertainty.
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Authors who are presenting talks have a * after their name.
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