TheoremBase

Proof

We use claims 2 and 4 of Basic Properties of a Measure (monotonicity and countable subadditivity of PP, 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).

Step 1 (claim 1). Let q=(c,j)∈Lq=(c,j)\in\mathsf{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 cc the variables KcK^{c}, (Vic)i(V^{c}_i)_i, (Uic,j′)j′,i(U^{c,j'}_i)_{j',i} with the cells Ic,1,…,Ic,JcI_{c,1},\dots,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 Kc,j\mathsf{K}_{c,j} is the cell count CjC_j of that lemma; by its claim 2, CjC_j has the Poisson distribution with parameter ∣Ij∣=∣Ic,j∣=μq|I_j|=|I_{c,j}|=\mu_q. Now let m<μq\mathsf{m}<\mu_q and put x=μq−m>0x=\mu_q-\mathsf{m}>0. Claim 3 of Series Formula, Exponential Moments, and Chernoff Tail Bounds for the Poisson Distribution, applied to the Poisson variable Kq\mathsf{K}_q with parameter μq\mu_q, gives P(Kq≤μq−x)≤exp⁡(−ϖμq(x))P(\mathsf{K}_q\le\mu_q-x)\le\exp(-\varpi_{\mu_q}(x)), and μq−x=m\mu_q-x=\mathsf{m}. Since {Kq<m}⊆{Kq≤m}\{\mathsf{K}_q<\mathsf{m}\}\subseteq\{\mathsf{K}_q\le\mathsf{m}\}, monotonicity gives P(Kq<m)≤exp⁡(−ϖμq(μq−m))P(\mathsf{K}_q<\mathsf{m})\le\exp(-\varpi_{\mu_q}(\mu_q-\mathsf{m})).

Step 2 (claim 2). Assume R∈NR\in\mathbb{N}, M∈NM\in\mathbb{N} with L≤ML\le M, and D>2D>2; put x=D−2>0x=D-2>0. For each label c∈Lc\in\mathcal{L} we construct an event GcG_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=Rn=R (a natural number with n≤Rn\le R), the process P♯,c\mathsf{P}^{\sharp,c} satisfies the hypotheses of Uniform Window Discrepancy Bound for a Counting Process with Poisson Increments on the Integer Grid with n=Rn=R; apply that lemma with its window length taken to be MM and with this xx. It yields an event Gc∈FG_c\in\mathcal{F} (it lies in the σ\sigma-algebra generated by P0♯,c,…,PR♯,c\mathsf{P}^{\sharp,c}_0,\dots,\mathsf{P}^{\sharp,c}_R, a sub-σ\sigma-algebra of F\mathcal{F}) with P(Ω∖Gc)≤2 (R+1)(M+3)exp⁡(−ϖM+2(D−2))P(\Omega\setminus G_c)\le2\,(R+1)(M+3)\exp\bigl(-\varpi_{M+2}(D-2)\bigr) such that for every ω∈Gc\omega\in G_c and all real 0≤u≤u′≤R0\le u\le u'\le R with u′−u≤Mu'-u\le M, ∣Pu′♯,c(ω)−Pu♯,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 . Now let ω∈Ω0U∩⋂c∈LGc\omega\in\Omega^{U}_0\cap\bigcap_{c\in\mathcal{L}}G_c. For every label cc and all real 0≤u≤u′≤R0\le u\le u'\le R with u′−u≤Lu'-u\le L we have u′−u≤Mu'-u\le 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∈Ω0U\omega\in\Omega^{U}_0 satisfying exactly these bounds), ω∈GL,D\omega\in G_{L,D}. Hence Ω∖GL,D⊆(Ω∖Ω0U)∪⋃c∈L(Ω∖Gc).\Omega\setminus G_{L,D}\subseteq(\Omega\setminus\Omega^{U}_0)\cup\bigcup_{c\in\mathcal{L}}(\Omega\setminus G_c). The set GL,DG_{L,D} belongs to F\mathcal{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∖Ω0U)=1−P(Ω0U)=0P(\Omega\setminus\Omega^{U}_0)=1-P(\Omega^{U}_0)=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) labels give P(Ω∖GL,D)≤0+∑c∈LP(Ω∖Gc)≤2 l(l−1) (R+1)(M+3)exp⁡(−ϖM+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).

Step 3 (claim 3). Each Kq\mathsf{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 {Kq≥m}∈F\{\mathsf{K}_q\ge\mathsf{m}\}\in\mathcal{F}, and Gm=GL,D∩⋂q∈L{Kq≥m}G^{\mathsf{m}}=G_{L,D}\cap\bigcap_{q\in\mathsf{L}}\{\mathsf{K}_q\ge\mathsf{m}\} is a finite intersection of members of F\mathcal{F}, hence in F\mathcal{F}. Its complement is Ω∖Gm=(Ω∖GL,D)∪⋃q∈L{Kq<m},\Omega\setminus G^{\mathsf{m}}=(\Omega\setminus G_{L,D})\cup\bigcup_{q\in\mathsf{L}}\{\mathsf{K}_q<\mathsf{m}\}, so by subadditivity, claim 1 (applicable since m<μq\mathsf{m}<\mu_q for every qq) and claim 2, P(Ω∖Gm)≤P(Ω∖GL,D)+∑q∈LP(Kq<m)≤2 l(l−1) (R+1)(M+3)exp⁡(−ϖM+2(D−2))+∑q∈Lexp⁡(−ϖμq(μq−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).

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