We use claims 2 and 4 of Basic Properties of a Measure (monotonicity and countable subadditivity of P P P , a finite union being a sequence padded with the empty set) and claim 3 of that lemma in the form P ( Ω ∖ A ) = 1 − P ( A ) P(\Omega\setminus A)=1-P(A) P ( Ω ∖ A ) = 1 − P ( A ) .
Step 1 (claim 1). Let q = ( c , j ) ∈ L q=(c,j)\in\mathsf{L} q = ( c , j ) ∈ L . By The Synthetic Copy: Independent Cell Structure, Deterministic-Count Clocks, the Copy Measure, and the Smoothed Joint Density of Parameter and Observation Record , for the label c c c the variables K c K^{c} K c , ( V i c ) i (V^{c}_i)_i ( V i c ) i , ( U i c , j ′ ) j ′ , i (U^{c,j'}_i)_{j',i} ( U i c , j ′ ) j ′ , i with the cells I c , 1 , … , I c , J c I_{c,1},\dots,I_{c,J_c} I c , 1 , … , I c , J c form the data 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 , and K c , j \mathsf{K}_{c,j} K c , j is the cell count C j C_j C j of that lemma; by its claim 2, C j C_j C j has the Poisson distribution with parameter ∣ I j ∣ = ∣ I c , j ∣ = μ q |I_j|=|I_{c,j}|=\mu_q ∣ I j ∣ = ∣ I c , j ∣ = μ q . Now let m < μ q \mathsf{m}<\mu_q m < μ q and put x = μ q − m > 0 x=\mu_q-\mathsf{m}>0 x = μ q − m > 0 . Claim 3 of Series Formula, Exponential Moments, and Chernoff Tail Bounds for the Poisson Distribution , applied to the Poisson variable K q \mathsf{K}_q K q with parameter μ q \mu_q μ q , gives P ( K q ≤ μ q − x ) ≤ exp ( − ϖ μ q ( x ) ) P(\mathsf{K}_q\le\mu_q-x)\le\exp(-\varpi_{\mu_q}(x)) P ( K q ≤ μ q − x ) ≤ exp ( − ϖ μ q ( x )) , and μ q − x = m \mu_q-x=\mathsf{m} μ q − x = m . Since { K q < m } ⊆ { K q ≤ m } \{\mathsf{K}_q<\mathsf{m}\}\subseteq\{\mathsf{K}_q\le\mathsf{m}\} { K q < m } ⊆ { K q ≤ m } , monotonicity gives P ( K q < m ) ≤ exp ( − ϖ μ q ( μ q − m ) ) P(\mathsf{K}_q<\mathsf{m})\le\exp(-\varpi_{\mu_q}(\mu_q-\mathsf{m})) P ( K q < m ) ≤ exp ( − ϖ μ q ( μ q − m )) .
Step 2 (claim 2). Assume R ∈ N R\in\mathbb{N} R ∈ N , M ∈ N M\in\mathbb{N} M ∈ N with L ≤ M L\le M L ≤ M , and D > 2 D>2 D > 2 ; put x = D − 2 > 0 x=D-2>0 x = D − 2 > 0 . For each label c ∈ L c\in\mathcal{L} c ∈ L we construct an event G c G_c G c as follows. By claim 3 of The Copy Clocks Have Independent Poisson Increments on the Clock Interval: Law Identity with the Uniform Poisson Path and Applicability of the Window Discrepancy Bound with n = R n=R n = R (a natural number with n ≤ R n\le R n ≤ R ), the process P ♯ , c \mathsf{P}^{\sharp,c} P ♯ , c satisfies the hypotheses of Uniform Window Discrepancy Bound for a Counting Process with Poisson Increments on the Integer Grid with n = R n=R n = R ; apply that lemma with its window length taken to be M M M and with this x x x . It yields an event G c ∈ F G_c\in\mathcal{F} G c ∈ F (it lies in the σ \sigma σ -algebra generated by P 0 ♯ , c , … , P R ♯ , c \mathsf{P}^{\sharp,c}_0,\dots,\mathsf{P}^{\sharp,c}_R P 0 ♯ , c , … , P R ♯ , c , a sub-σ \sigma σ -algebra of F \mathcal{F} F ) with
P ( Ω ∖ G c ) ≤ 2 ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) ) P(\Omega\setminus G_c)\le2\,(R+1)(M+3)\exp\bigl(-\varpi_{M+2}(D-2)\bigr) P ( Ω ∖ G c ) ≤ 2 ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) )
such that for every ω ∈ G c \omega\in G_c ω ∈ G c and all real 0 ≤ u ≤ u ′ ≤ R 0\le u\le u'\le R 0 ≤ u ≤ u ′ ≤ R with u ′ − u ≤ M u'-u\le M u ′ − u ≤ M ,
∣ P u ′ ♯ , c ( ω ) − P u ♯ , c ( ω ) − ( u ′ − u ) ∣ ≤ x + 2 = D . \bigl|\mathsf{P}^{\sharp,c}_{u'}(\omega)-\mathsf{P}^{\sharp,c}_{u}(\omega)-(u'-u)\bigr|\le x+2=D . P u ′ ♯ , c ( ω ) − P u ♯ , c ( ω ) − ( u ′ − u ) ≤ x + 2 = D .
Now let ω ∈ Ω 0 U ∩ ⋂ c ∈ L G c \omega\in\Omega^{U}_0\cap\bigcap_{c\in\mathcal{L}}G_c ω ∈ Ω 0 U ∩ ⋂ c ∈ L G c . For every label c c c and all real 0 ≤ u ≤ u ′ ≤ R 0\le u\le u'\le R 0 ≤ u ≤ u ′ ≤ R with u ′ − u ≤ L u'-u\le L u ′ − u ≤ L we have u ′ − u ≤ M u'-u\le M u ′ − u ≤ M , so the displayed bound holds; by the definition of the clock-good event in Uniform Pair-Exponent Bound on the Synthetic Copy: Removed-Clock Intensities, the Insertion Response on the Clock-Good Event, and Bounds on the Pair Covariances (the set of ω ∈ Ω 0 U \omega\in\Omega^{U}_0 ω ∈ Ω 0 U satisfying exactly these bounds), ω ∈ G L , D \omega\in G_{L,D} ω ∈ G L , D . Hence
Ω ∖ G L , D ⊆ ( Ω ∖ Ω 0 U ) ∪ ⋃ c ∈ L ( Ω ∖ G c ) . \Omega\setminus G_{L,D}\subseteq(\Omega\setminus\Omega^{U}_0)\cup\bigcup_{c\in\mathcal{L}}(\Omega\setminus G_c). Ω ∖ G L , D ⊆ ( Ω ∖ Ω 0 U ) ∪ ⋃ c ∈ L ( Ω ∖ G c ) .
The set G L , D G_{L,D} G L , D belongs to F \mathcal{F} F by claim 1 of Uniform Pair-Exponent Bound on the Synthetic Copy: Removed-Clock Intensities, the Insertion Response on the Clock-Good Event, and Bounds on the Pair Covariances , and P ( Ω ∖ Ω 0 U ) = 1 − P ( Ω 0 U ) = 0 P(\Omega\setminus\Omega^{U}_0)=1-P(\Omega^{U}_0)=0 P ( Ω ∖ Ω 0 U ) = 1 − P ( Ω 0 U ) = 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 . Monotonicity and subadditivity over the l ( l − 1 ) l(l-1) l ( l − 1 ) labels give
P ( Ω ∖ G L , D ) ≤ 0 + ∑ c ∈ L P ( Ω ∖ G c ) ≤ 2 l ( l − 1 ) ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) ) . P(\Omega\setminus G_{L,D})\le0+\sum_{c\in\mathcal{L}}P(\Omega\setminus G_c)\le2\,l(l-1)\,(R+1)(M+3)\exp\bigl(-\varpi_{M+2}(D-2)\bigr). P ( Ω ∖ G L , D ) ≤ 0 + ∑ c ∈ L P ( Ω ∖ G c ) ≤ 2 l ( l − 1 ) ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) ) .
Step 3 (claim 3). Each K q \mathsf{K}_q K q is a random variable (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 { K q ≥ m } ∈ F \{\mathsf{K}_q\ge\mathsf{m}\}\in\mathcal{F} { K q ≥ m } ∈ F , and G m = G L , D ∩ ⋂ q ∈ L { K q ≥ m } G^{\mathsf{m}}=G_{L,D}\cap\bigcap_{q\in\mathsf{L}}\{\mathsf{K}_q\ge\mathsf{m}\} G m = G L , D ∩ ⋂ q ∈ L { K q ≥ m } is a finite intersection of members of F \mathcal{F} F , hence in F \mathcal{F} F . Its complement is
Ω ∖ G m = ( Ω ∖ G L , D ) ∪ ⋃ q ∈ L { K q < m } , \Omega\setminus G^{\mathsf{m}}=(\Omega\setminus G_{L,D})\cup\bigcup_{q\in\mathsf{L}}\{\mathsf{K}_q<\mathsf{m}\}, Ω ∖ G m = ( Ω ∖ G L , D ) ∪ ⋃ q ∈ L { K q < m } ,
so by subadditivity, claim 1 (applicable since m < μ q \mathsf{m}<\mu_q m < μ q for every q q q ) and claim 2,
P ( Ω ∖ G m ) ≤ P ( Ω ∖ G L , D ) + ∑ q ∈ L P ( K q < m ) ≤ 2 l ( l − 1 ) ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) ) + ∑ q ∈ L exp ( − ϖ μ q ( μ q − m ) ) . P(\Omega\setminus G^{\mathsf{m}})\le P(\Omega\setminus G_{L,D})+\sum_{q\in\mathsf{L}}P(\mathsf{K}_q<\mathsf{m})\le2\,l(l-1)\,(R+1)(M+3)\exp\bigl(-\varpi_{M+2}(D-2)\bigr)+\sum_{q\in\mathsf{L}}\exp\bigl(-\varpi_{\mu_q}(\mu_q-\mathsf{m})\bigr). P ( Ω ∖ G m ) ≤ P ( Ω ∖ G L , D ) + ∑ q ∈ L P ( K q < m ) ≤ 2 l ( l − 1 ) ( R + 1 ) ( M + 3 ) exp ( − ϖ M + 2 ( D − 2 ) ) + ∑ q ∈ L exp ( − ϖ μ q ( μ q − m ) ) .