A Weighted Error Distance Metrics (WEDM) for Performance Evaluation on Multiple Change-Point (MCP) Detection in Synthetic Time Series

<div>The repetitive simulations of single CP detection on 100 time series from one of 10 tests in Exp1, with random parameter values of sample size <i>N</i> <i>=</i> 2^14, actual <i>tCP</i> = 12267, and variance (V) = 1.9. By using different TST, BST, KS, T, and SSA models, the simulation results including (a) locations, (b) distributions, (c) frequency, and (d) WED of the resultant eCPs are represented in line with the test number, time-series positions, NPED, and NNED in the <i>x</i>-axis, respectively.</div>

Computational Intelligence and Neuroscience

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Figure 9

Figure 9: A Weighted Error Distance Metrics (WEDM) for Performance Evaluation on Multiple Change-Point (MCP) Detection in Synthetic Time Series 