Maintained by ppernot
This module enables to plot the distribution of errors (as histogram) and to explore the trends of error sets.
Select: select the error set
Remove glob. outl.: remove global outliers (if any)
defined in module Outliers
# Hist classes: number of classes in the histogram
(defaults to Scott’s method when slider set to 0)
Normal fit: draw a normal fit to the errors histogram
Plot trend line: plot the trend line for a polynomial
defined by Trend degree
Correct trend: correct the errors from the trend line
Trend degree: degree of the polynomial trend line
Bland-Altman: plot Bland-Altman statistics (2.5% and
97.5% interval + mean) with their bootstrapped uncertainty
Tag outliers: plot the tags of points out of the 95%
confidence interval defined by the Bland-Altman lines
Glob. errror scale: scale the y-axis from the full dataset
(all methods) or from the current one
The left panel presents a histogram of the errors and oprionally a normal fit (same mean and variance). The histogram reflects the transformations to the errors set (outliers removal, trend correction…)
The right panel plots the errors as a function of the calculated data in order to visualize trends that might be corrected to improve predictions.