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Activity Number:
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203
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 3, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #304652 |
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Title:
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Time-Frequency Methods for Space-Time Models
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Author(s):
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Peter F. Craigmile*+
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Companies:
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The Ohio State University
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Address:
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The Department of Statistics, Columbus, OH, 43210,
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Keywords:
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space-time processes ; spectral analysis ; wavelet analysis ; environmental statistics
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Abstract:
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In many scientific areas, we study the interaction between phenomena observed in space and time, or some transformation of time. Consider data observed continuously in space, but discretely and regularly in time. We apply spectral and wavelet methods to the analysis of such space-time data. A spectral analysis is used to explore features of a statistical process in the frequency domain in terms of a linear combination of complex exponentials (sinusoids). A wavelet analysis provides a space/time-scale (approximately a space/time-frequency) decomposition of a statistical process in terms of averages and changes of averages over different temporal or spatial scales. We discuss spectral and wavelet-based methods that can be used for exploratory data analysis, as well as for inference with space-time processes. We apply these methods to the analysis of space-time environmental data.
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