Skip to main content
Figure 4 | BMC Bioinformatics

Figure 4

From: Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

Figure 4

Identifying extreme outliers. This shows the first of 5000 simulated data sets with a single outlier (open symbol) whose distance from the ideal curve equations 7 times the standard deviation of the Gaussian scatter of the rest of the points. Our method detected an outlier like this in all but 5 of 5000 simulated data sets, while falsely defining very few good points to be an outlier (False Discovery Rate = 1.18%).

Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us