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The density ratio is undefined on zero marginal fibres

Statement refuted

False assertion: a joint probability density always defines its conditional density by the ratio p(x,y)/p(t,y)dt at every y.

Assume AC for the compact integration bridge. The uniform joint density p(x,y)=1(0,1)(x)1(0,1)(y) on the unit square refutes this at y=2. The constant uniform-on-(0,1) probability kernel is nevertheless a valid measurable conditional extension.

Facts & Assumptions

Given: The hypotheses and conventions in the statement refuted.

[F1]

The conditional density theorem normalizes only finite positive marginal fibres and permits a fixed probability filler elsewhere. Conditional density formula.

[F2]

An extension must have probability sections and measurable evaluations everywhere. Measure kernel and probability kernel.

[F4]

The compact integral agrees with its Lebesgue integral under countable choice. A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral.

[F5]

AC supplies the countable-choice bridge; no version selection is needed. The Axiom of Choice.

[F6]

Tonelli computes this nonnegative product density and its marginal. Tonelli's theorem for nonnegative measurable functions on a sigma-finite product.

[F7]

The square density and the interval density define measures. The indefinite integral of a nonnegative measurable function is a measure.

Counterexample

technique · direct
1.1

The density p is the indicator of a Borel rectangle. By [F3]–[F5], 011dx=1; endpoints have measure zero by containment in intervals with arbitrarily small lengths. Tonelli [F6] gives total joint mass 11=1 and marginal m(y)=1(0,1)(y). The measure construction is [F7]. At y=2, p(x,2)=0 for every x and m(2)=0. The asserted quotient is therefore 0/0, which is undefined, at every x on that fibre. Thus the claimed everywhere formula fails for a fully normalized bounded joint density.

F3F4F5F6F7
2.1

Put ρ(A)=λ1(A(0,1)) and K(y,A)=ρ(A) for all real y. By [F7] and the mass calculation, rho is a probability, and constant evaluations are measurable, proving [F2]. On 0<y<1 this agrees with the density ratio. On its complement it is the supplied filler allowed by [F1]. Directly, for Borel A,B, BK(y,A)PY(dy)=λ1(A(0,1))λ1(B(0,1))=P(XA,YB), with the last equality from [F6]. So the extension is a conditional law, including an everywhere probability section at y=2. For example K(2,(0,1/2))=1/2, a chosen valid extension value, not a value of 0/0.

step 1.1F1F2F6F7

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