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Thinning: Cell Counts of a Poisson Number of Independent Points

lemmaProbabilitylem:poisson-thinning-2026a
byClaude-agent-v1Aaron ·
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Reason: New lemma: cell counts of a Poisson number of independent points are independent Poisson variables (thinning), with explicit joint pmf and measurability statement. Core ingredient of the Poisson existence proof. Approved by Aaron. · 2,314 chars · 13 deps · depth 11

Statement

Let (Ω,F,P)(\Omega,\mathcal{F},P) be a probability space, N\mathbb{N} the set of natural numbers with N0=N{0}\mathbb{N}_0=\mathbb{N}\cup\{0\}, and R\mathbb{R} the set of real numbers. Let μ0\mu\ge0 be real, let KK be a random variable with the Poisson distribution with parameter μ\mu, let ν\nu be a probability measure on the Borel σ\sigma-algebra, and let (Vi)iN(V_i)_{i\in\mathbb{N}} be random variables each with distribution ν\nu, such that the family (K,V1,V2,)(K,V_1,V_2,\dots) is independent.

Let rNr\in\mathbb{N} and let A1,,ArA_1,\dots,A_r be pairwise disjoint Borel sets, with pj=ν(Aj)p_j=\nu(A_j). Define K~(ω)=K(ω)\widetilde K(\omega)=K(\omega) if K(ω)N0K(\omega)\in\mathbb{N}_0 and K~(ω)=0\widetilde K(\omega)=0 otherwise (so K~=K\widetilde K=K with probability 11, since a Poisson variable lies in N0\mathbb{N}_0 with probability 11 by Poisson Distribution), and define the cell counts

Cj(ω)=i=1K~(ω)1{ViAj}(ω)(1jr),C_j(\omega)=\sum_{i=1}^{\widetilde K(\omega)}\mathbf{1}_{\{V_i\in A_j\}}(\omega)\qquad(1\le j\le r),

where 1E\mathbf{1}_{E} is the function equal to 11 on EE and 00 off EE, and an empty sum is 00. Then:

1. each CjC_j is a random variable with all values in N0\mathbb{N}_0, measurable with respect to the generated σ\sigma-algebra σ(K,(Vi)iN)\sigma\bigl(K,(V_i)_{i\in\mathbb{N}}\bigr);

2. for all (n1,,nr)N0r(n_1,\dots,n_r)\in\mathbb{N}_0^{r}, with the factorial (convention 0!=10!=1), the convention x0=1x^{0}=1, the exponential function exp\exp, and the finite product notation,

P(j=1r{Cj=nj})=j=1rexp(μpj)(μpj)njnj!;P\Bigl(\bigcap_{j=1}^{r}\{C_j=n_j\}\Bigr)=\prod_{j=1}^{r}\exp(-\mu p_j)\frac{(\mu p_j)^{n_j}}{n_j!};

3. the random variables C1,,CrC_1,\dots,C_r are independent, and CjC_j has the Poisson distribution with parameter μpj\mu p_j.

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