Extremal analysis of processes sampled at different frequencies

The observed extremes of a discrete time process depend on the process itself and the sampling frequency. We develop theoretical results which show how to account for the effect of sampling frequency on extreme values, thus enabling us to analyse systematically extremal data from series with differe...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2000, Vol.62 (1), p.117-135
Main Authors: Robinson, M. E., Tawn, J. A.
Format: Article
Language:English
Subjects:
Approximation
Data analysis
Data sampling
Distribution
Distribution functions
Exact sciences and technology
Extremal index
Extreme value theory
Generalized extreme value distribution
Mathematical analysis
Mathematical maxima
Mathematics
Probability and statistics
Probability theory and stochastic processes
Rain
Rainfall
Samples
Sampling frequency
Sampling rates
Sciences and techniques of general use
Series convergence
Stochastic processes
Tidal waves
Time dependence
Time series
Values
Waves
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Description
Summary:The observed extremes of a discrete time process depend on the process itself and the sampling frequency. We develop theoretical results which show how to account for the effect of sampling frequency on extreme values, thus enabling us to analyse systematically extremal data from series with different sampling rates. We present statistical methodology based on these results which we illustrate though simulations and by applications to sea-waves and rainfall data.
ISSN:1369-7412
1467-9868
DOI:10.1111/1467-9868.00223