Estimate moments from sampleΒΆ

In this example we are going to estimate statistical moments from a sample, eventually from an output variable of interest.

import openturns as ot

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

Create a sample

# model f
model = ot.SymbolicFunction(["x1", "x2"], ["x1^2+x2", "x2^2+x1"])

# input vector X
inputDist = ot.ComposedDistribution([ot.Normal()] * 2, ot.IndependentCopula(2))
inputDist.setDescription(["X1", "X2"])
inputVector = ot.RandomVector(inputDist)

# output vector Y=f(X)
output = ot.CompositeRandomVector(model, inputVector)

# sample Y
size = 1000
sample = output.getSample(size)

Estimate mean

sample.computeMean()

[0.922665,1.02048]



Estimate standard deviation

sample.computeStandardDeviation()

[1.65284,1.81903]



Estimate variance

sample.computeVariance()

[2.73188,3.30888]



Estimate skewness

sample.computeSkewness()

[1.45099,1.73197]



Estimate kurtosis

sample.computeKurtosis()

[7.06969,7.94102]



Total running time of the script: ( 0 minutes 0.005 seconds)