TheoremBase

Predictable-Window Moment Identities for the Homogeneous Poisson Process

Statement

Let (Ω,F,P)(\Omega,\mathcal{F},P) be a probability space and let Y=(Yu)u≥0Y=(Y_u)_{u\ge0} be a homogeneous Poisson process with rate 11 on it, all of whose paths are counting paths. For every natural number p≥1p\ge1 let μp:[0,∞)→[0,∞]\mu_p:[0,\infty)\to[0,\infty] be given by μp(x)=∫R∣t∣p dPx(t)\mu_p(x)=\int_{\mathbb{R}}|t|^{p}\,dP_x(t), the Lebesgue integral of the nonnegative measurable map t↦∣t∣pt\mapsto|t|^{p} with respect to the Poisson distribution PxP_x with parameter xx. Write exp⁡\exp for the real exponential function and E\mathbb{E} for the expectation, expectations of [0,∞][0,\infty]-valued random variables being their integrals with respect to PP.

Fix real numbers θ≥0\theta\ge0, Vˉ≥θ\bar{V}\ge\theta, and Λˉ≥0\bar{\Lambda}\ge0, and a σ\sigma-algebra G⊆F\mathcal{G}\subseteq\mathcal{F} that is independent of the σ\sigma-algebra σ(Yθ+s−Yθ: s≥0)\sigma(Y_{\theta+s}-Y_{\theta}:\ s\ge0) generated by the increments of YY beyond θ\theta. Let vv and λ\lambda be G\mathcal{G}-measurable random variables with θ≤v(ω)≤Vˉ\theta\le v(\omega)\le\bar{V} and 0≤λ(ω)≤Λˉ0\le\lambda(\omega)\le\bar{\Lambda} for every ω\omega.

1. (Evaluation at random levels) For every random variable w≥0w\ge0 on (Ω,F,P)(\Omega,\mathcal{F},P) the map ω↦Yw(ω)(ω)\omega\mapsto Y_{w(\omega)}(\omega) is a random variable, and for random variables 0≤w≤w′0\le w\le w' the increment Yw′−YwY_{w'}-Y_{w} is a random variable with values in the nonnegative integers. Moreover, if G0⊆F\mathcal{G}_0\subseteq\mathcal{F} is a σ\sigma-algebra such that ww is G0\mathcal{G}_0-measurable and YuY_u is G0\mathcal{G}_0-measurable for every real u≥0u\ge0, then YwY_{w} is G0\mathcal{G}_0-measurable.

2. (Window moments) For every natural number p≥1p\ge1 and every G\mathcal{G}-measurable Z:Ω→[0,∞]Z:\Omega\to[0,\infty], E[Z (Yv+λ−Yv)p]=E[Z μp(λ)]in [0,∞].\mathbb{E}\bigl[Z\,\bigl(Y_{v+\lambda}-Y_{v}\bigr)^{p}\bigr]=\mathbb{E}\bigl[Z\,\mu_p(\lambda)\bigr]\qquad\text{in }[0,\infty].

3. (Window events) For every G\mathcal{G}-measurable Z:Ω→[0,∞]Z:\Omega\to[0,\infty], E[Z 1{Yv+λ−Yv≥1}]=E[Z (1−exp⁡(−λ))]≤E[Z λ]in [0,∞].\mathbb{E}\bigl[Z\,\mathbf{1}\{Y_{v+\lambda}-Y_{v}\ge1\}\bigr]=\mathbb{E}\bigl[Z\,\bigl(1-\exp(-\lambda)\bigr)\bigr]\le\mathbb{E}\bigl[Z\,\lambda\bigr]\qquad\text{in }[0,\infty].

4. (Moment functions) For every natural number p≥1p\ge1 and every x≥0x\ge0, μp(x)=exp⁡(−x)∑k≥1kp xkk!<∞,\mu_p(x)=\exp(-x)\sum_{k\ge1}\frac{k^{p}\,x^{k}}{k!}<\infty, the sum over the natural numbers k≥1k\ge1 being well-defined by nonnegativity as the least upper bound of its finite partial sums, with the factorial k!k!; moreover μ1(x)=x\mu_1(x)=x for every x≥0x\ge0; each μp\mu_p is nondecreasing and continuous on [0,∞)[0,\infty); and μp(x)≤cp x\mu_p(x)\le c_p\,x for every x∈[0,1]x\in[0,1], where cp=∑k≥1kp/k!c_p=\sum_{k\ge1}k^{p}/k! is finite.

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