Copula fitting test using Kendall plotΒΆ

In this example we are going to perform a visual goodness-of-fit test for a copula with the Kendall plot test.

from __future__ import print_function
import openturns as ot
import openturns.viewer as viewer
from matplotlib import pylab as plt

Create two samples

N = 500

dist1 = ot.ComposedDistribution([ot.Normal()] * 2, ot.GumbelCopula(3.0))
sample1 = dist1.getSample(N)

dist2 = ot.ComposedDistribution([ot.Normal()] * 2, ot.ClaytonCopula(0.2))
sample2 = dist2.getSample(N)

Change the parameter for the evaluation of E(Wi)

ot.ResourceMap.SetAsUnsignedInteger('VisualTest-KendallPlot-MonteCarloSize', 25)

Test a specific copula model for a given sample

copula_test = ot.GumbelCopula(3)
graph = ot.VisualTest.DrawKendallPlot(sample1, copula_test)
view =viewer.View(graph)
Kendall Plot

Test whether two samples have the same copula model

graph = ot.VisualTest.DrawKendallPlot(sample1, sample2)
view = viewer.View(graph)
Kendall Plot

Total running time of the script: ( 0 minutes 0.478 seconds)

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