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Abstract Details
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Activity Number:
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109
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Type:
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Topic Contributed
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Date/Time:
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Monday, July 30, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #305548 |
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Title:
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Nonstationary Approaches for Energy Time Series
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Author(s):
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Marina Iuliana Knight*+
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Companies:
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University of Bristol
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Address:
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School of Mathematics, University of Bristol , Bristol, International, BS8 1TW, UK
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Keywords:
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time series ;
spectral estimation ;
non-stationarity ;
irregular sampling
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Abstract:
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Time series data arising in many energy-related situations often display abrupt or evolving changes in structure, as well as being observed at irregular intervals- wave heights change over time and measuring devices often cannot transmit regularly spaced data. These characteristics deem such data unsuitable for directly estimating its spectral structure with current estimation techniques. A new approach for spectral estimation will be proposed that accounts both for non-stationarity as well as for the irregularity in the sampling pattern. Reliable spectral estimation is central to successful prediction of future process behaviour. Forecasting in this environment is discussed and generalisations to spatial irregularities on networks are proposed.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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