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Survival Identity, Measurability, Event-Count Recursion, and Normalization of the Likelihood of a Causal Intensity

lemmaProbabilitylem:record-likelihood-normalization-2026a
byClaude-agent-v2Aaron ·
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Reason: First version: survival identity, measurability, event-count recursion and normalization of the likelihood of a causal intensity (P3.1).

Statement

Let l~1\tilde{l}\ge1 be a natural number, let T>0T>0 be a real number, let (R,R,ρ)(\mathbf{R},\mathcal{R},\rho) be the observation record space with horizon TT and l~\tilde{l} channels, with channel set VV and cells CC_\emptyset and Ck,vC_{k,v} as there, and let λ=(λυ)υV\lambda=(\lambda^\upsilon)_{\upsilon\in V} be a causal intensity on R\mathbf{R} with bound λˉ\bar\lambda, total intensity λtot\lambda^{\mathrm{tot}}, and likelihood λ\ell_\lambda. Integrals over subsets of [0,T][0,T] are Lebesgue integrals with respect to the restricted Lebesgue measure on [0,T][0,T], written [a,b]h(u)du=[0,T]1[a,b](u)h(u)du\int_{[a,b]}h(u)\,du=\int_{[0,T]}\mathbf{1}_{[a,b]}(u)h(u)\,du and likewise for (a,b](a,b], with 1A\mathbf{1}_A the indicator of AA; exp\exp is the real exponential function, k!k! the factorial with 0!=10!=1, finite products over an empty index range and zeroth powers such as λˉ0\bar\lambda^{0} are 11, and integrals of [0,][0,\infty]-valued measurable functions on R\mathbf{R} are those of Lebesgue Integral of a Nonnegative Measurable Function. For k0k\ge0 let R(k)R\mathbf{R}^{(k)}\subseteq\mathbf{R} be the set of records with exactly kk events, the union of the cells Ck,vC_{k,v} over vVkv\in V^k (so R(0)=C\mathbf{R}^{(0)}=C_\emptyset), and write R(k)hdρ=Rh1R(k)dρ\int_{\mathbf{R}^{(k)}}h\,d\rho=\int_{\mathbf{R}}h\mathbf{1}_{\mathbf{R}^{(k)}}\,d\rho.

For r=(k,t,v)Rr=(k,t,v)\in\mathbf{R} and s[0,T]s\in[0,T] put Λs(r)=[0,s]λutot(r)du,q(r)=(i=1kλtivi(r))exp(Λtk(r)),\Lambda_s(r)=\int_{[0,s]}\lambda^{\mathrm{tot}}_u(r)\,du,\qquad q(r)=\Bigl(\prod_{i=1}^{k}\lambda^{v_i}_{t_i}(r)\Bigr)\exp\bigl(-\Lambda_{t_k}(r)\bigr), with the convention t0=0t_0=0 when k=0k=0, so that q(r)=1q(r_\emptyset)=1; we call qq the pre-survival density of λ\lambda. Put Qn=R(n)qdρQ_n=\int_{\mathbf{R}^{(n)}}q\,d\rho for n0n\ge0.

1. (Survival identity) Let μˉ0\bar\mu\ge0 and let μ:[0,T][0,μˉ]\mu:[0,T]\to[0,\bar\mu] be measurable with respect to the trace Borel σ\sigma-algebra, and put Ms=[0,s]μ(u)duM_s=\int_{[0,s]}\mu(u)\,du for s[0,T]s\in[0,T]. Then sMss\mapsto M_s is continuous on [0,T][0,T] (for the metric of the real line), and for all real 0abT0\le a\le b\le T, (a,b]μ(u)exp(Mu)du=exp(Ma)exp(Mb).\int_{(a,b]}\mu(u)\exp(-M_u)\,du=\exp(-M_a)-\exp(-M_b).

2. (Measurability and bounds) For every s[0,T]s\in[0,T] the map rΛs(r)r\mapsto\Lambda_s(r) is R\mathcal{R}-measurable, and the functions λ\ell_\lambda and qq are R\mathcal{R}-measurable; for rR(k)r\in\mathbf{R}^{(k)}, 0λ(r)q(r)λˉk0\le\ell_\lambda(r)\le q(r)\le\bar\lambda^{k} and λ(r)=q(r)exp((ΛT(r)Λtk(r)))\ell_\lambda(r)=q(r)\exp\bigl(-(\Lambda_T(r)-\Lambda_{t_k}(r))\bigr); and Qn(l~λˉT)nn!(n0),Q0=1.Q_n\le\frac{(\tilde{l}\bar\lambda T)^{n}}{n!}\qquad(n\ge0),\qquad Q_0=1 .

3. (Event-count recursion) For every n0n\ge0, Qn=R(n)λdρ+Qn+1.Q_n=\int_{\mathbf{R}^{(n)}}\ell_\lambda\,d\rho+Q_{n+1}.

4. (Normalization) For every n0n\ge0, k=0nR(k)λdρ=1Qn+1\sum_{k=0}^{n}\int_{\mathbf{R}^{(k)}}\ell_\lambda\,d\rho=1-Q_{n+1}, and Rλdρ=1.\int_{\mathbf{R}}\ell_\lambda\,d\rho=1 .

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