Throughout, measurable for a real-valued map means measurable with respect to the Borel σ \sigma σ -algebra on the target; expectations and integrals of [ 0 , ∞ ] [0,\infty] [ 0 , ∞ ] -valued measurable maps are those of Lebesgue Integral of a Nonnegative Measurable Function . We use freely the following two facts. (Q1) If Z n : X → [ 0 , ∞ ] Z_n:X\to[0,\infty] Z n : X → [ 0 , ∞ ] (n ∈ N n\in\mathbb{N} n ∈ N ) are measurable on a measure space ( X , X , ν ) (X,\mathcal{X},\nu) ( X , X , ν ) , then ∑ n Z n \sum_nZ_n ∑ n Z n is measurable and ∫ ∑ n Z n d ν = ∑ n ∫ Z n d ν \int\sum_nZ_n\,d\nu=\sum_n\int Z_n\,d\nu ∫ ∑ n Z n d ν = ∑ n ∫ Z n d ν (partial sums increase to the sum; Linearity and Monotonicity of the Lebesgue Integral and Monotone Convergence Theorem ). (Q2) N 0 L \mathbb{N}_0^{\mathsf{L}} N 0 L is countable (it is the set of values of a sequence, listing for n = 0 , 1 , 2 , … n=0,1,2,\dots n = 0 , 1 , 2 , … the finitely many y y y with ∑ ( c , j ) y c , j = n \sum_{(c,j)}y_{c,j}=n ∑ ( c , j ) y c , j = n ), so sums over y ∈ N 0 L y\in\mathbb{N}_0^{\mathsf{L}} y ∈ N 0 L of nonnegative terms, in the sense of Sum of a Nonnegative Function over an Arbitrary Set , are sequential sums along this enumeration, and they are invariant under the bijective reindexing x = y / N x=y/\sqrt{N} x = y / N between N 0 L \mathbb{N}_0^{\mathsf{L}} N 0 L and S \mathsf{S} S (both being least upper bounds of finite partial sums, as in the preamble of Assembly of Measure Spaces: Restriction, Transport, One-Point Spaces, and Countable Disjoint Unions ). Finally, for y ∈ N 0 L y\in\mathbb{N}_0^{\mathsf{L}} y ∈ N 0 L the indicator 1 { K = y } \mathbf{1}\{\mathsf{K}=y\} 1 { K = y } is V \mathcal{V} V -measurable and P ( K = y ) = ∏ ( c ′ , j ′ ) ∈ L p o i μ c ′ , j ′ ( y c ′ , j ′ ) > 0 P(\mathsf{K}=y)=\prod_{(c',j')\in\mathsf{L}}\mathrm{poi}_{\mu_{c',j'}}(y_{c',j'})>0 P ( K = y ) = ∏ ( c ′ , j ′ ) ∈ L poi μ c ′ , j ′ ( y c ′ , j ′ ) > 0 , by claim 1 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record , and E [ 1 { K = y } Z ] = P ( K = y ) E [ Z ] \mathbb{E}[\mathbf{1}\{\mathsf{K}=y\}Z]=P(\mathsf{K}=y)\mathbb{E}[Z] E [ 1 { K = y } Z ] = P ( K = y ) E [ Z ] for every U \mathcal{U} U -measurable Z : Ω → [ 0 , ∞ ] Z:\Omega\to[0,\infty] Z : Ω → [ 0 , ∞ ] (the factorisation of that claim).
Step 1 (claim 1: removed clocks). Fix ( c , j ) (c,j) ( c , j ) and ω \omega ω with K c , j ( ω ) ≥ m \mathsf{K}_{c,j}(\omega)\ge\mathsf{m} K c , j ( ω ) ≥ m and put y = K ( ω ) − m e c , j y=\mathsf{K}(\omega)-\mathsf{m}e_{c,j} y = K ( ω ) − m e c , j , a point of N 0 L \mathbb{N}_0^{\mathsf{L}} N 0 L with y + m e c , j = K ( ω ) y+\mathsf{m}e_{c,j}=\mathsf{K}(\omega) y + m e c , j = K ( ω ) and y c , j = K c , j ( ω ) − m y_{c,j}=\mathsf{K}_{c,j}(\omega)-\mathsf{m} y c , j = K c , j ( ω ) − m . By the definition of the copy clocks, P ♯ ( ω ) = P ( K ( ω ) ) ( ω ) = P ( y + m e c , j ) ( ω ) \mathsf{P}^{\sharp}(\omega)=\mathsf{P}^{(\mathsf{K}(\omega))}(\omega)=\mathsf{P}^{(y+\mathsf{m}e_{c,j})}(\omega) P ♯ ( ω ) = P ( K ( ω )) ( ω ) = P ( y + m e c , j ) ( ω ) , and claim 2 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record (insertion, with ( c 0 , j 0 ) = ( c , j ) (c_0,j_0)=(c,j) ( c 0 , j 0 ) = ( c , j ) ) gives exactly the two displayed identities, the inserted points being U i c , j ( ω ) U^{c,j}_i(\omega) U i c , j ( ω ) for y c , j < i ≤ y c , j + m y_{c,j}<i\le y_{c,j}+\mathsf{m} y c , j < i ≤ y c , j + m , together with their location and distinctness on Ω 0 U \Omega^{U}_0 Ω 0 U . The identification of ℓ − ( c , j ) , ω = ℓ ( y ) , ω \ell^{-(c,j),\omega}=\ell^{(y),\omega} ℓ − ( c , j ) , ω = ℓ ( y ) , ω as the likelihood for the clocks P ( y ) ( ω ) \mathsf{P}^{(y)}(\omega) P ( y ) ( ω ) is claim 3 of that lemma.
Step 2 (claim 2: measurability and moments). The removed-clock likelihood. For every ( r , ω ) (r,\omega) ( r , ω ) ,
ℓ − ( c , j ) , ω ( r ) = ∑ y ∈ N 0 L : y c , j ≥ m 1 { K ( ω ) = y } ℓ ( y − m e c , j ) , ω ( r ) , \ell^{-(c,j),\omega}(r)=\sum_{y\in\mathbb{N}_0^{\mathsf{L}}:\ y_{c,j}\ge\mathsf{m}}\mathbf{1}\{\mathsf{K}(\omega)=y\}\,\ell^{(y-\mathsf{m}e_{c,j}),\omega}(r), ℓ − ( c , j ) , ω ( r ) = ∑ y ∈ N 0 L : y c , j ≥ m 1 { K ( ω ) = y } ℓ ( y − m e c , j ) , ω ( r ) ,
since at most one term is nonzero, namely the one with y = K ( ω ) y=\mathsf{K}(\omega) y = K ( ω ) , present exactly when K c , j ( ω ) ≥ m \mathsf{K}_{c,j}(\omega)\ge\mathsf{m} K c , j ( ω ) ≥ m . Each term is the product of the R ⊗ F \mathcal{R}\otimes\mathcal{F} R ⊗ F -measurable maps ( r , ω ) ↦ 1 { K ( ω ) = y } (r,\omega)\mapsto\mathbf{1}\{\mathsf{K}(\omega)=y\} ( r , ω ) ↦ 1 { K ( ω ) = y } (indicator of the measurable rectangle R × { K = y } \mathbf{R}\times\{\mathsf{K}=y\} R × { K = y } ) and ( r , ω ) ↦ ℓ ( y − m e c , j ) , ω ( r ) (r,\omega)\mapsto\ell^{(y-\mathsf{m}e_{c,j}),\omega}(r) ( r , ω ) ↦ ℓ ( y − m e c , j ) , ω ( r ) (R ⊗ U \mathcal{R}\otimes\mathcal{U} R ⊗ U -measurable by claim 3 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record , hence R ⊗ F \mathcal{R}\otimes\mathcal{F} R ⊗ F -measurable since U ⊆ F \mathcal{U}\subseteq\mathcal{F} U ⊆ F ), hence measurable by claims 1 and 3 of Arithmetic, Absolute Values, and Pointwise Limits of Measurable Real-Valued Functions ; the countable sum, whose partial sums along the enumeration of (Q2) converge pointwise in R \mathbb{R} R (at most one term being nonzero), is measurable by claim 5 of Arithmetic, Absolute Values, and Pointwise Limits of Measurable Real-Valued Functions . The bound ( N B ~ ) k (N\tilde{B})^{k} ( N B ~ ) k on R ( k ) × Ω \mathbf{R}^{(k)}\times\Omega R ( k ) × Ω is inherited from the same claim 3.
The removal ratio. K c , j \mathsf{K}_{c,j} K c , j is V \mathcal{V} V -measurable with values in N 0 \mathbb{N}_0 N 0 (claim 1 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record ), so ϱ c , j ( K c , j ) = ∑ k ∈ N 0 ϱ c , j ( k ) 1 { K c , j = k } \varrho_{c,j}(\mathsf{K}_{c,j})=\sum_{k\in\mathbb{N}_0}\varrho_{c,j}(k)\mathbf{1}\{\mathsf{K}_{c,j}=k\} ϱ c , j ( K c , j ) = ∑ k ∈ N 0 ϱ c , j ( k ) 1 { K c , j = k } , a pointwise limit in R \mathbb{R} R of finite sums of V \mathcal{V} V -measurable maps (exactly one term is nonzero), is V \mathcal{V} V -measurable by claim 5 of Arithmetic, Absolute Values, and Pointwise Limits of Measurable Real-Valued Functions , with finite values. By (Q1), E [ ϱ c , j ( K c , j ) ] = ∑ k ϱ c , j ( k ) P ( K c , j = k ) \mathbb{E}[\varrho_{c,j}(\mathsf{K}_{c,j})]=\sum_k\varrho_{c,j}(k)P(\mathsf{K}_{c,j}=k) E [ ϱ c , j ( K c , j )] = ∑ k ϱ c , j ( k ) P ( K c , j = k ) and E [ ϱ c , j ( K c , j ) 2 ] = ∑ k ϱ c , j ( k ) 2 P ( K c , j = k ) \mathbb{E}[\varrho_{c,j}(\mathsf{K}_{c,j})^{2}]=\sum_k\varrho_{c,j}(k)^{2}P(\mathsf{K}_{c,j}=k) E [ ϱ c , j ( K c , j ) 2 ] = ∑ k ϱ c , j ( k ) 2 P ( K c , j = k ) . Since K c , j \mathsf{K}_{c,j} K c , j has the Poisson distribution with parameter μ c , j \mu_{c,j} μ c , j (claim 2 of Uniform Representation of the Rate-One Poisson Counting Path on a Bounded Interval: Distinct Points, Poisson Increments, Conditional Law Given the Cell Counts, and Point Insertion , K c , j \mathsf{K}_{c,j} K c , j being a cell count of that lemma by the preamble of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record ), P ( K c , j = k ) = p o i μ c , j ( k ) P(\mathsf{K}_{c,j}=k)=\mathrm{poi}_{\mu_{c,j}}(k) P ( K c , j = k ) = poi μ c , j ( k ) , and claims 2 and 3 of The Poisson Removal Ratio for Moves of Several Points: Move Score, Mean, Exact Second Moment, Move Information, and Pointwise Bounds give the two displayed values.
The composed functional. By claim 2(a) of Weighted Cauchy-Schwarz Inequality on a Measure Space and the Symmetrised Score Functional: Bounds and Averaging , Φ w \Phi_w Φ w is sequentially continuous on [ 0 , ∞ ) 1 + d [0,\infty)^{1+d} [ 0 , ∞ ) 1 + d . The 1 + d 1+d 1 + d components ( r , ω ) ↦ ℓ ♯ , ω ( r ) (r,\omega)\mapsto\ell^{\sharp,\omega}(r) ( r , ω ) ↦ ℓ ♯ , ω ( r ) (claim 3 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record ) and ( r , ω ) ↦ ϱ c , j ( K c , j ( ω ) ) ℓ − ( c , j ) , ω ( r ) (r,\omega)\mapsto\varrho_{c,j}(\mathsf{K}_{c,j}(\omega))\ell^{-(c,j),\omega}(r) ( r , ω ) ↦ ϱ c , j ( K c , j ( ω )) ℓ − ( c , j ) , ω ( r ) (products of the measurable maps above, the factor ϱ c , j ( K c , j ) \varrho_{c,j}(\mathsf{K}_{c,j}) ϱ c , j ( K c , j ) being V \mathcal{V} V -measurable, hence F \mathcal{F} F -measurable as V ⊆ F \mathcal{V}\subseteq\mathcal{F} V ⊆ F , and composed with the second projection R × Ω → Ω \mathbf{R}\times\Omega\to\Omega R × Ω → Ω ) are R ⊗ F \mathcal{R}\otimes\mathcal{F} R ⊗ F -measurable with values in [ 0 , ∞ ) [0,\infty) [ 0 , ∞ ) , so the composition with Φ w \Phi_w Φ w is measurable by Sequentially Continuous Functions of Measurable Euclidean Maps are Measurable (with E = [ 0 , ∞ ) 1 + d E=[0,\infty)^{1+d} E = [ 0 , ∞ ) 1 + d ), with values in [ 0 , ∞ ) [0,\infty) [ 0 , ∞ ) .
Step 3 (claim 3: the shifted family). Fix x = y / N ∈ S x=y/\sqrt{N}\in\mathsf{S} x = y / N ∈ S , r ∈ R r\in\mathbf{R} r ∈ R and ( c , j ) ∈ L (c,j)\in\mathsf{L} ( c , j ) ∈ L . Unshifted. By definition, p ( x ) f ( x , r ) = P ( K = y ) E [ ℓ ( y ) , ⋅ ( r ) ] = E [ 1 { K = y } ℓ ( y ) , ⋅ ( r ) ] \mathsf{p}(x)f(x,r)=P(\mathsf{K}=y)\,\mathbb{E}[\ell^{(y),\cdot}(r)]=\mathbb{E}[\mathbf{1}\{\mathsf{K}=y\}\ell^{(y),\cdot}(r)] p ( x ) f ( x , r ) = P ( K = y ) E [ ℓ ( y ) , ⋅ ( r )] = E [ 1 { K = y } ℓ ( y ) , ⋅ ( r )] by the factorisation (the map ω ↦ ℓ ( y ) , ω ( r ) \omega\mapsto\ell^{(y),\omega}(r) ω ↦ ℓ ( y ) , ω ( r ) being U \mathcal{U} U -measurable as the section at r r r of an R ⊗ U \mathcal{R}\otimes\mathcal{U} R ⊗ U -measurable map: the sets whose section at r r r lies in U \mathcal{U} U form a σ \sigma σ -algebra containing the measurable rectangles, hence containing R ⊗ U \mathcal{R}\otimes\mathcal{U} R ⊗ U by Intersections of Sigma-Algebras and Minimality of the Generated Sigma-Algebra ), and on { K = y } \{\mathsf{K}=y\} { K = y } one has ℓ ( y ) , ω = ℓ ♯ , ω \ell^{(y),\omega}=\ell^{\sharp,\omega} ℓ ( y ) , ω = ℓ ♯ , ω by claim 3 of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record ; this is the first identity.
Shifted. By Gaussian Smoothing of a Kernel-Weighted Discrete Family with Countable Support: Joint Density, van Trees Regularity, and the Symmetrised Directional Score Bound , p c , j ( x ) = p ( x − a c , j ) \mathsf{p}_{c,j}(x)=\mathsf{p}(x-a_{c,j}) p c , j ( x ) = p ( x − a c , j ) and f c , j ( x , r ) = f ( x − a c , j , r ) f_{c,j}(x,r)=f(x-a_{c,j},r) f c , j ( x , r ) = f ( x − a c , j , r ) if x − a c , j ∈ S x-a_{c,j}\in\mathsf{S} x − a c , j ∈ S , f c , j ( x , r ) = 0 f_{c,j}(x,r)=0 f c , j ( x , r ) = 0 otherwise. Here x − a c , j = ( y − m e c , j ) / N x-a_{c,j}=(y-\mathsf{m}e_{c,j})/\sqrt{N} x − a c , j = ( y − m e c , j ) / N , which lies in S \mathsf{S} S if and only if y c , j ≥ m y_{c,j}\ge\mathsf{m} y c , j ≥ m .
Case y c , j < m y_{c,j}<\mathsf{m} y c , j < m . Then x − a c , j ∉ S x-a_{c,j}\notin\mathsf{S} x − a c , j ∈ / S , so p c , j ( x ) = 0 \mathsf{p}_{c,j}(x)=0 p c , j ( x ) = 0 (p \mathsf{p} p vanishes off S \mathsf{S} S ) and the left side is 0 0 0 ; on the right, ϱ c , j ( K c , j ) = ϱ c , j ( y c , j ) = 0 \varrho_{c,j}(\mathsf{K}_{c,j})=\varrho_{c,j}(y_{c,j})=0 ϱ c , j ( K c , j ) = ϱ c , j ( y c , j ) = 0 on { K = y } \{\mathsf{K}=y\} { K = y } , so the expectation is 0 0 0 .
Case y c , j ≥ m y_{c,j}\ge\mathsf{m} y c , j ≥ m . Put y ′ = y − m e c , j ∈ N 0 L y'=y-\mathsf{m}e_{c,j}\in\mathbb{N}_0^{\mathsf{L}} y ′ = y − m e c , j ∈ N 0 L . Then p c , j ( x ) f c , j ( x , r ) = p ( y ′ / N ) f ( y ′ / N , r ) = P ( K = y ′ ) E [ ℓ ( y ′ ) , ⋅ ( r ) ] \mathsf{p}_{c,j}(x)f_{c,j}(x,r)=\mathsf{p}(y'/\sqrt{N})f(y'/\sqrt{N},r)=P(\mathsf{K}=y')\,\mathbb{E}[\ell^{(y'),\cdot}(r)] p c , j ( x ) f c , j ( x , r ) = p ( y ′ / N ) f ( y ′ / N , r ) = P ( K = y ′ ) E [ ℓ ( y ′ ) , ⋅ ( r )] . In the product formula for P ( K = y ′ ) P(\mathsf{K}=y') P ( K = y ′ ) and P ( K = y ) P(\mathsf{K}=y) P ( K = y ) all factors agree except the one indexed by ( c , j ) (c,j) ( c , j ) , whence P ( K = y ′ ) = P ( K = y ) p o i μ c , j ( y c , j − m ) / p o i μ c , j ( y c , j ) = P ( K = y ) ϱ c , j ( y c , j ) P(\mathsf{K}=y')=P(\mathsf{K}=y)\,\mathrm{poi}_{\mu_{c,j}}(y_{c,j}-\mathsf{m})/\mathrm{poi}_{\mu_{c,j}}(y_{c,j})=P(\mathsf{K}=y)\varrho_{c,j}(y_{c,j}) P ( K = y ′ ) = P ( K = y ) poi μ c , j ( y c , j − m ) / poi μ c , j ( y c , j ) = P ( K = y ) ϱ c , j ( y c , j ) . Hence, by the factorisation applied to the U \mathcal{U} U -measurable map ω ↦ ℓ ( y ′ ) , ω ( r ) \omega\mapsto\ell^{(y'),\omega}(r) ω ↦ ℓ ( y ′ ) , ω ( r ) and by Linearity and Monotonicity of the Lebesgue Integral for the constant ϱ c , j ( y c , j ) \varrho_{c,j}(y_{c,j}) ϱ c , j ( y c , j ) ,
p c , j ( x ) f c , j ( x , r ) = ϱ c , j ( y c , j ) E [ 1 { K = y } ℓ ( y ′ ) , ⋅ ( r ) ] = E [ 1 { K = y } ϱ c , j ( K c , j ) ℓ − ( c , j ) , ⋅ ( r ) ] , \mathsf{p}_{c,j}(x)f_{c,j}(x,r)=\varrho_{c,j}(y_{c,j})\,\mathbb{E}\bigl[\mathbf{1}\{\mathsf{K}=y\}\ell^{(y'),\cdot}(r)\bigr]=\mathbb{E}\bigl[\mathbf{1}\{\mathsf{K}=y\}\varrho_{c,j}(\mathsf{K}_{c,j})\ell^{-(c,j),\cdot}(r)\bigr], p c , j ( x ) f c , j ( x , r ) = ϱ c , j ( y c , j ) E [ 1 { K = y } ℓ ( y ′ ) , ⋅ ( r ) ] = E [ 1 { K = y } ϱ c , j ( K c , j ) ℓ − ( c , j ) , ⋅ ( r ) ] ,
since on { K = y } \{\mathsf{K}=y\} { K = y } one has ϱ c , j ( K c , j ) = ϱ c , j ( y c , j ) \varrho_{c,j}(\mathsf{K}_{c,j})=\varrho_{c,j}(y_{c,j}) ϱ c , j ( K c , j ) = ϱ c , j ( y c , j ) and ℓ − ( c , j ) , ω = ℓ ( K ( ω ) − m e c , j ) , ω = ℓ ( y ′ ) , ω \ell^{-(c,j),\omega}=\ell^{(\mathsf{K}(\omega)-\mathsf{m}e_{c,j}),\omega}=\ell^{(y'),\omega} ℓ − ( c , j ) , ω = ℓ ( K ( ω ) − m e c , j ) , ω = ℓ ( y ′ ) , ω .
Step 4 (claim 4: the reduction). Let Ψ \Psi Ψ be the pathwise score map of the statement, which is R ⊗ F \mathcal{R}\otimes\mathcal{F} R ⊗ F -measurable and [ 0 , ∞ ) [0,\infty) [ 0 , ∞ ) -valued by Step 2; the measurability of r ↦ E [ Ψ ( r , ⋅ ) ] r\mapsto\mathbb{E}[\Psi(r,\cdot)] r ↦ E [ Ψ ( r , ⋅ )] and of ω ↦ ∫ R Ψ ( r , ω ) ρ ( d r ) \omega\mapsto\int_{\mathbf{R}}\Psi(r,\omega)\rho(dr) ω ↦ ∫ R Ψ ( r , ω ) ρ ( d r ) asserted in claim 2 is the Tonelli theorem on R × Ω \mathbf{R}\times\Omega R × Ω .
One lattice point. Fix x = y / N ∈ S x=y/\sqrt{N}\in\mathsf{S} x = y / N ∈ S and r ∈ R r\in\mathbf{R} r ∈ R . Define on ( Ω , F , P ) (\Omega,\mathcal{F},P) ( Ω , F , P ) the maps ℓ 0 ( ω ) = 1 { K ( ω ) = y } ℓ ♯ , ω ( r ) \ell_0(\omega)=\mathbf{1}\{\mathsf{K}(\omega)=y\}\ell^{\sharp,\omega}(r) ℓ 0 ( ω ) = 1 { K ( ω ) = y } ℓ ♯ , ω ( r ) and ℓ c , j ( ω ) = 1 { K ( ω ) = y } ϱ c , j ( K c , j ( ω ) ) ℓ − ( c , j ) , ω ( r ) \ell_{c,j}(\omega)=\mathbf{1}\{\mathsf{K}(\omega)=y\}\varrho_{c,j}(\mathsf{K}_{c,j}(\omega))\ell^{-(c,j),\omega}(r) ℓ c , j ( ω ) = 1 { K ( ω ) = y } ϱ c , j ( K c , j ( ω )) ℓ − ( c , j ) , ω ( r ) , ( c , j ) ∈ L (c,j)\in\mathsf{L} ( c , j ) ∈ L . They are measurable (sections at r r r of the measurable maps of Step 2, by the section argument of Step 3, times indicators), nonnegative, and bounded (by ( N B ~ ) k (N\tilde{B})^{k} ( N B ~ ) k for r ∈ R ( k ) r\in\mathbf{R}^{(k)} r ∈ R ( k ) , respectively by ϱ c , j ( y c , j ) ( N B ~ ) k \varrho_{c,j}(y_{c,j})(N\tilde{B})^{k} ϱ c , j ( y c , j ) ( N B ~ ) k ), hence have finite integrals, which by Step 3 are A = E [ ℓ 0 ] = p ( x ) f ( x , r ) A=\mathbb{E}[\ell_0]=\mathsf{p}(x)f(x,r) A = E [ ℓ 0 ] = p ( x ) f ( x , r ) and B c , j = E [ ℓ c , j ] = p c , j ( x ) f c , j ( x , r ) B_{c,j}=\mathbb{E}[\ell_{c,j}]=\mathsf{p}_{c,j}(x)f_{c,j}(x,r) B c , j = E [ ℓ c , j ] = p c , j ( x ) f c , j ( x , r ) . Claim 3 of Weighted Cauchy-Schwarz Inequality on a Measure Space and the Symmetrised Score Functional: Bounds and Averaging (averaging inequality, on the measure space ( Ω , F , P ) (\Omega,\mathcal{F},P) ( Ω , F , P ) ) gives
Φ w ( p ( x ) f ( x , r ) , ( p c , j ( x ) f c , j ( x , r ) ) ( c , j ) ) ≤ E [ Φ w ( ℓ 0 , ( ℓ c , j ) ( c , j ) ) ] = E [ 1 { K = y } Ψ ( r , ⋅ ) ] , \Phi_w\bigl(\mathsf{p}(x)f(x,r),(\mathsf{p}_{c,j}(x)f_{c,j}(x,r))_{(c,j)}\bigr)\le\mathbb{E}\bigl[\Phi_w(\ell_0,(\ell_{c,j})_{(c,j)})\bigr]=\mathbb{E}\bigl[\mathbf{1}\{\mathsf{K}=y\}\,\Psi(r,\cdot)\bigr], Φ w ( p ( x ) f ( x , r ) , ( p c , j ( x ) f c , j ( x , r ) ) ( c , j ) ) ≤ E [ Φ w ( ℓ 0 , ( ℓ c , j ) ( c , j ) ) ] = E [ 1 { K = y } Ψ ( r , ⋅ ) ] ,
where the last equality is pointwise in ω \omega ω : by the homogeneity of claim 2(c) of Weighted Cauchy-Schwarz Inequality on a Measure Space and the Symmetrised Score Functional: Bounds and Averaging with the factor 1 { K ( ω ) = y } ∈ { 0 , 1 } \mathbf{1}\{\mathsf{K}(\omega)=y\}\in\{0,1\} 1 { K ( ω ) = y } ∈ { 0 , 1 } , Φ w ( ℓ 0 ( ω ) , ( ℓ c , j ( ω ) ) ( c , j ) ) = 1 { K ( ω ) = y } Ψ ( r , ω ) \Phi_w(\ell_0(\omega),(\ell_{c,j}(\omega))_{(c,j)})=\mathbf{1}\{\mathsf{K}(\omega)=y\}\Psi(r,\omega) Φ w ( ℓ 0 ( ω ) , ( ℓ c , j ( ω ) ) ( c , j ) ) = 1 { K ( ω ) = y } Ψ ( r , ω ) .
Summation. By the definition of J s y m \mathsf{J}^{\mathrm{sym}} J sym in Gaussian Smoothing of a Kernel-Weighted Discrete Family with Countable Support: Joint Density, van Trees Regularity, and the Symmetrised Directional Score Bound (whose claim 1 gives the R \mathcal{R} R -measurability in r r r of its integrand for each x x x ), the monotonicity of the integral (Linearity and Monotonicity of the Lebesgue Integral ) and of sums of nonnegative terms, and the reindexing (Q2),
J s y m = ∑ x ∈ S ∫ R Φ w ( p ( x ) f ( x , r ) , ( p c , j ( x ) f c , j ( x , r ) ) ( c , j ) ) ρ ( d r ) ≤ ∑ y ∈ N 0 L ∫ R E [ 1 { K = y } Ψ ( r , ⋅ ) ] ρ ( d r ) , \mathsf{J}^{\mathrm{sym}}=\sum_{x\in\mathsf{S}}\int_{\mathbf{R}}\Phi_w\bigl(\mathsf{p}(x)f(x,r),(\mathsf{p}_{c,j}(x)f_{c,j}(x,r))_{(c,j)}\bigr)\rho(dr)\le\sum_{y\in\mathbb{N}_0^{\mathsf{L}}}\int_{\mathbf{R}}\mathbb{E}\bigl[\mathbf{1}\{\mathsf{K}=y\}\Psi(r,\cdot)\bigr]\rho(dr), J sym = ∑ x ∈ S ∫ R Φ w ( p ( x ) f ( x , r ) , ( p c , j ( x ) f c , j ( x , r ) ) ( c , j ) ) ρ ( d r ) ≤ ∑ y ∈ N 0 L ∫ R E [ 1 { K = y } Ψ ( r , ⋅ ) ] ρ ( d r ) ,
the map r ↦ E [ 1 { K = y } Ψ ( r , ⋅ ) ] r\mapsto\mathbb{E}[\mathbf{1}\{\mathsf{K}=y\}\Psi(r,\cdot)] r ↦ E [ 1 { K = y } Ψ ( r , ⋅ )] being R \mathcal{R} R -measurable by the Tonelli theorem on R × Ω \mathbf{R}\times\Omega R × Ω (ρ \rho ρ is σ \sigma σ -finite by the preamble of The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record , P P P is finite). Applying (Q1) twice (first for ρ \rho ρ , then for P P P ) and using ∑ y 1 { K = y } = 1 \sum_y\mathbf{1}\{\mathsf{K}=y\}=1 ∑ y 1 { K = y } = 1 pointwise (K \mathsf{K} K takes values in N 0 L \mathbb{N}_0^{\mathsf{L}} N 0 L ), the right side equals
∫ R E [ ∑ y 1 { K = y } Ψ ( r , ⋅ ) ] ρ ( d r ) = ∫ R E [ Ψ ( r , ⋅ ) ] ρ ( d r ) = E [ ∫ R Ψ ( r , ⋅ ) ρ ( d r ) ] , \int_{\mathbf{R}}\mathbb{E}\Bigl[\sum_{y}\mathbf{1}\{\mathsf{K}=y\}\Psi(r,\cdot)\Bigr]\rho(dr)=\int_{\mathbf{R}}\mathbb{E}[\Psi(r,\cdot)]\,\rho(dr)=\mathbb{E}\Bigl[\int_{\mathbf{R}}\Psi(r,\cdot)\,\rho(dr)\Bigr], ∫ R E [ ∑ y 1 { K = y } Ψ ( r , ⋅ ) ] ρ ( d r ) = ∫ R E [ Ψ ( r , ⋅ )] ρ ( d r ) = E [ ∫ R Ψ ( r , ⋅ ) ρ ( d r ) ] ,
the last equality being Tonelli on R × Ω \mathbf{R}\times\Omega R × Ω for the nonnegative R ⊗ F \mathcal{R}\otimes\mathcal{F} R ⊗ F -measurable Ψ \Psi Ψ . ■ \blacksquare ■