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(i) Three classical offline outlier detection algorithms adapted to perform online outlier detection.
To enhance the chance of detecting rare CNVs and CN classes we perform a recursive outlier detection using Grubbs test [39] for single sample outlier detection.
After analyzing several outlier detection measures, we found that Cook's distance (CDISS) performed well for outlier detection.
Robust regression and outlier detection.
Consequently, real-time outlier detection is realized by a distance-based outlier detection algorithm.
The RANSAC algorithm is employed for outlier detection.
To compare the performance of Grubbs' outlier detection procedure with recursive Extreme Studentized Deviate (ESD) outlier detection procedure.
These facts motivate the new outlier detection method that we have developed here.
Hubert, M., Rousseeuw, P. J. & Segaert, P. Multivariate functional outlier detection.
Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.
A technique is developed, based on novel signal processing and statistical outlier detection.
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