Note

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Fit a parametric copulaΒΆ

In this example we are going to estimate the parameters of a gaussian copula from a sample.

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

ot.Log.Show(ot.Log.NONE)

Create data

R = ot.CorrelationMatrix(2)
R[1, 0] = 0.4
copula = ot.NormalCopula(R)
sample = copula.getSample(500)

Estimate a normal copula

distribution = ot.NormalCopulaFactory().build(sample)
print(distribution)

NormalCopula(R = [[ 1        0.501533 ]
 [ 0.501533 1        ]])

The estimated parameters

distribution.getParameter()

[0.501533]



Draw fitted distribution

graph = distribution.drawPDF()
view = viewer.View(graph)
plt.show()
[X0,X1] iso-PDF