Fit a parametric copula

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

from __future__ import print_function
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)

Out:

NormalCopula(R = [[ 1        0.427237 ]
 [ 0.427237 1        ]])

The estimated parameters

distribution.getParameter()

[0.427237]

Draw fitted distribution

graph = distribution.drawPDF()
view = viewer.View(graph)
plt.show()