Figure 9.

Stability diagnostic plot of the identification procedure on multiscale sets of experiments. Multiscale unbiased joint inclusion probability estimates is plotted against a range of experimental scale values <a onClick="popup('http://www.biomedcentral.com/1471-2105/13/128/mathml/M261','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/128/mathml/M261">View MathML</a> for an arbitrary marginal inclusion probability threshold of <a onClick="popup('http://www.biomedcentral.com/1471-2105/13/128/mathml/M262','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/128/mathml/M262">View MathML</a>. The plot also displays probability estimate standard errors, the change point <a onClick="popup('http://www.biomedcentral.com/1471-2105/13/128/mathml/M263','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/128/mathml/M263">View MathML</a> (<a onClick="popup('http://www.biomedcentral.com/1471-2105/13/128/mathml/M264','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/128/mathml/M264">View MathML</a>) and the scatterplot smoothing curves fitted to the data (by LOESS local polynomial regression procedure). These curves are approximately horizontal-flat (i.e. show no trend) for K > Kmin.

Dazard et al. BMC Bioinformatics 2012 13:128   doi:10.1186/1471-2105-13-128
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