Confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine

Authors:
Qiang Cheng;Jale Tezcan;Jie Cheng
Affiliations:
-;-;-
Venue:
Pattern Recognition Letters
Year:
2014

Citing 5
Cited 0

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Abstract

We consider estimating the confidence and prediction intervals for semiparametric mixed-effect least squares support vector machine (LS-SVM). Explicit formulas are derived for confidence and prediction intervals. The accuracy of the derived analytical equations is assessed by comparing with wild cluster bootstrap-t method on simulated and real-world data with different levels of random-effect and residual variances, and different numbers of clusters. Close match between the derived expressions and the bootstrap results is observed.