Show that if xi is a random variable in L^2(F) and G is a sigma -field contained in F, then E(xi|G) is the orthogonal projection of xi onto the subspace L^2(G) in L^2(F) consisting of G-measurable random variables.

rustenig

rustenig

Answered question

2022-09-04

Show that if ξ is a random variable in L 2 ( F ) and G is a σ -field contained in F, then E ( ξ | G ) is the orthogonal projection of ξ onto the subspace L 2 ( G ) in L 2 ( F ) consisting of G-measurable random variables.

Answer & Explanation

enreciarpv

enreciarpv

Beginner2022-09-05Added 18 answers

Step 1
Recall that for a Hilbert space H and its closed, convex, non-empty subset C the projection of a point x on to C is the unique point y C such that x y = inf z C x z .
I will write PG for the orthogonal projection on to L 2 ( G ) . We want to show P G ξ = E [ ξ | G ] almost surely.
Let Y = P G ξ and take Z L 2 ( G ) . Consider W = Y + a Z L 2 ( G ) for a R . It follows from the definition of the projection that
0 ξ W L 2 ( F ) 2 ξ Y L 2 ( F ) 2 = a 2 E [ Z 2 ] 2 a E [ ( ξ Y ) Z ]
The right hand side is a quadratic in a which is non-negative for all a iff E [ ( ξ Y ) Z ] = 0 so ξ Y L 2 ( G ) . (This is a special case of the more general fact that if P is an orthogonal projection on to a subspace U of a Hilbert space H then for x H , x P x U )
By considering Z of the form 1 A for A G , it immediately follows that Y is a version of E [ ξ | G ] and we are done.

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