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Activity Number:
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138
- Digging into Models: Statistical Theory Inspired by Environmental Applications
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Type:
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Invited
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #309349
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Title:
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Inverse and Decorrelating Operators for Matern Covariances
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Author(s):
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Joseph Guinness*
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Companies:
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Cornell University
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Keywords:
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Abstract:
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This paper presents some theory for understanding the behavior of entries of the inverse of Matern covariance matrices and decorrelating transforms for data with Matern covariances. We also present efficient algorithms for numerical computation of the inverse and decorrelating operators and compare them to existing methods for approximating the inverses. We discuss how the methods can be used to quickly decorrelate data and estimate covariance parameters from data.
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Authors who are presenting talks have a * after their name.
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