Author: Emma Southall; Michael J. Tildesley; Louise Dyson
Title: Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data Document date: 2020_4_2
ID: dp4qv77q_43
Snippet: where two points in the time series (t 1 , x t1 ) and (t 2 , x t2 ) with t 1 < t 2 are said to be a 301 concordant pair if x t1 < x t2 , and a discordant pair if x t1 > x t2 . If the two points are 302 equal (x t1 = x t2 ) then the pair is neither concordant or discordant. 303 We calculate each statistic on a moving window (size 50) for each detrended 304 simulation, and then evaluate the Kendall-tau score. We compare the Kendall-tau scores 305 c.....
Document: where two points in the time series (t 1 , x t1 ) and (t 2 , x t2 ) with t 1 < t 2 are said to be a 301 concordant pair if x t1 < x t2 , and a discordant pair if x t1 > x t2 . If the two points are 302 equal (x t1 = x t2 ) then the pair is neither concordant or discordant. 303 We calculate each statistic on a moving window (size 50) for each detrended 304 simulation, and then evaluate the Kendall-tau score. We compare the Kendall-tau scores 305 calculated on simulations going through a critical transition with null simulations, and 306 we then calculate receiver operating characteristic (ROC) curves by considering the null 307 model to be negative and the other models to be positive. We compare the performance 308 of each model statistic using the area under the curve (AUC). Good statistics have an 309 AUC close to 1 or 0 since this indicates the statistic is far from picking by chance.
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