This function returns the starting and ending points of events according to the noise test results from a time series.
Usage
eventExtraction(tests, w, alpha = 0.05)
Arguments
tests
test p values from the noist tests for the subsequences.
w
sliding window size.
alpha
the significance level. When the noise test p value of the subsequence is smaller than this significance level,
it is a potential event. Default is 0.05.
Value
a list consisting:
start
a vector consisting of starting points of events.
end
a vector consisting of ending points of events.
tests
smoothed test p value series.
nevents
number of detected events.
References
Yanfei Kang, Danijel Belusic, Kate Smith-Miles (2014): Detecting and Classifying Events in Noisy Time Series.
J. Atmos. Sci., 71, 1090-1104.
http://dx.doi.org/10.1175/JAS-D-13-0182.1.