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First and second moments of a Poisson random integral
Statement
Let be a Poisson point process with locally finite intensity measure . For every nonnegative Borel function , as identities in . Here and .
Facts & Assumptions
Given: A Poisson point process with locally finite intensity measure and a nonnegative Borel function .
Counts on disjoint Borel sets are independent and have Poisson laws with their intensity means; an infinite-mean count equals almost surely. (Poisson and Cox point processes)
For with finite , and . (The scalar Poisson count law, Normalization, moments, and generating function of the Poisson count law)
Nonnegative Borel functions admit increasing simple approximations, and increasing limits pass through nonnegative integrals. (Every nonnegative measurable function is the increasing limit of simple measurable functions, Monotone convergence for the integral)
Proof
First let be a nonnegative simple function with disjoint Borel sets and coefficients , after discarding zero coefficients. Write . If some , [F1] gives almost surely and both displayed right-hand quantities are infinite. If all , [F1]-[F2] give and . The zero simple function also satisfies both identities.
For arbitrary , choose simple by [F3]. Then , , , and . Applying monotone convergence [F3] to the two expectation integrals and to the two measure integrals, and using step 1.1 for each , yields both asserted identities, including the extended-infinite cases.
Depends on
- Random measures and locally finite point processes
- Poisson and Cox point processes
- The scalar Poisson count law
- Normalization, moments, and generating function of the Poisson count law
- Every nonnegative measurable function is the increasing limit of simple measurable functions
- Monotone convergence for the integral
Used by
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Sources
- Gunter Last and Mathew Penrose, Lectures on the Poisson Process, author-hosted 2017 version (standard reference, not scraped)