eventExtraction: Extract events from time series

In TED: Turbulence Time Series Event Detection and Classification

Description

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.

TED documentation built on May 2, 2019, 4:26 a.m.