Jacobi determinant


Let

f=f⁢(x)=f⁢(x1,…,xn)

be a function of n variables, and let

u=u⁢(x)=(u1⁢(x),…,un⁢(x))

be a function of x, where inversely x can be expressed as a function of u,

x=x⁢(u)=(x1⁢(u),…,xn⁢(u))

The formula for a change of variable in an n-dimensional integral is then

∫Ωf⁢(x)⁢dn⁢x=∫u⁢(Ω)f⁢(x⁢(u))⁢|det⁡(d⁢x/d⁢u)|⁢dn⁢u

Ω is an integration region, and one integrates over all x∈Ω, or equivalently, all u∈u⁢(Ω). d⁢x/d⁢u=(d⁢u/d⁢x)-1 is the Jacobi matrix and

|det⁡(d⁢x/d⁢u)|=|det⁡(d⁢u/d⁢x)|-1

is the absolute valuePlanetmathPlanetmath of the Jacobi determinant or Jacobian.

As an example, take n=2 and

Ω={(x1,x2)|0<x1≤1,0<x2≤1}

Define

ρ=-2⁢log⁡(x1)φ=2⁢π⁢x2u1=ρ⁢cos⁡φu2=ρ⁢sin⁡φ

Then by the chain rule and definition of the Jacobi matrix,

d⁢u/d⁢x = ∂⁡(u1,u2)/∂⁡(x1,x2)
= (∂⁡(u1,u2)/∂⁡(ρ,φ))⁢(∂⁡(ρ,φ)/∂⁡(x1,x2))
= (cos⁡φ-ρ⁢sin⁡φsin⁡φρ⁢cos⁡φ)⁢(-1/ρ⁢x1002⁢ϕ)

The Jacobi determinant is

det⁡(d⁢u/d⁢x) = det⁡{∂⁡(u1,u2)/∂⁡(ρ,φ)}⁢det⁡{∂⁡(ρ,φ)/∂⁡(x1,x2)}
= ρ⁢(-2⁢π/ρ⁢x1)=-2⁢π/xi

and

d2⁢x = |det⁡(d⁢x/d⁢u)|⁢d2⁢u=|det⁡(d⁢u/d⁢x)|-1⁢d2⁢u
= (x1/2⁢π)=(1/2⁢π)⁢exp⁡(-(u12+u22/2))⁢d2⁢u

This shows that if x1 and x2 are independentPlanetmathPlanetmath random variablesMathworldPlanetmath with uniform distributionsMathworldPlanetmath between 0 and 1, then u1 and u2 as defined above are independent random variables with standard normal distributionsMathworldPlanetmath.

References

  • •

    Originally from The Data Analysis Briefbook (http://rkb.home.cern.ch/rkb/titleA.htmlhttp://rkb.home.cern.ch/rkb/titleA.html)

Title Jacobi determinant
Canonical name JacobiDeterminant
Date of creation 2013-03-22 12:07:08
Last modified on 2013-03-22 12:07:08
Owner akrowne (2)
Last modified by akrowne (2)
Numerical id 8
Author akrowne (2)
Entry type Definition
Classification msc 62H05
Classification msc 15-00
Synonym Jacobian
Related topic ChainRuleSeveralVariables
Related topic MultidimensionalGaussianIntegral
Related topic ChangeOfVariablesInIntegralOnMathbbRn