Determining Jackknife ESS for a CTA Model with Chaotic Instability

Paul R. Yarnold

Optimal Data Analysis, LLC

CTA models are developed using one of three different strategies as concerns “leave-one-out” (LOO) analysis: (a) ignore LOO analysis; (b) only include attributes having identical ESS in training and LOO analysis in the model (the “LOO stable” criterion); or (c) only include attributes having the highest ESS in LOO analysis in the model (the “LOO p < 0.05” criterion). Software for performing CTA reports ESS for training but not for LOO analysis, so a recent article demonstrated the use of UniODA to assess ESS in LOO for CTA models with well-organized instability propagation—for example, restricted to a pair of endpoints for a node, or invalidating the CTA model for statistically unreliable replication. The present article illustrates assessing LOO ESS under chaotic conditions in which instability propagates down and across the left- and the right-hand sides of the CTA model.

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