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Activity Number:
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413
- Analyses of Environmental Data
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Type:
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Contributed
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Date/Time:
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Thursday, August 12, 2021 : 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 #318830
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Title:
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On Testing for the Equality of Autocovariance Between Time Series
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Author(s):
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Daniel Cirkovic and Thomas J Fisher*
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Companies:
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Texas A&M University and Miami University
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Keywords:
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Autocovariance;
Hypothesis test;
Multivariate Series;
Time Series
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Abstract:
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The comparison of two time series often arises in climatology, environmental science, and econometrics. Through natural and physical circumstances these series are often dependent. We study and develop a hypothesis test for the equality of autocovariance functions for two linearly dependent multivariate time series. Previous tests for two independent series are reviewed and extended to the dependent case. The performance of the tests are compared through simulation and the methods are applied to univariate temperature and multivariate air quality series. Empirical results show that by accounting for the correlation between series substantial improvements in power can be made in the detection of differences in the autocovariance.
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Authors who are presenting talks have a * after their name.
