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Pair-correlation density and Ripley K-function
Definition
Assume AC and Countable Choice as carried by the point-process and Palm suppliers. Let be stationary and locally square integrable as in Stationarity, finite intensity, and spatial ergodicity and Second factorial and reduced second factorial moment measures, with finite positive intensity and reduced second factorial moment measure .
A pair-correlation density exists exactly when is absolutely continuous with respect to Borel Lebesgue measure Lebesgue measurable sets, the family , and the restricted set function . Local finiteness makes sigma-finite, so A sigma-finite signed measure that is absolutely continuous with respect to a sigma-finite positive measure has a unique almost-everywhere density gives a density; positivity of the measure makes that density nonnegative almost everywhere, and replacing its values on the null exceptional set by zero gives a nonnegative Borel version. The density is unique up to Lebesgue-null sets. Normalize it by and call the resulting nonnegative Borel function :
for every Borel . The definition does not assume pair densities for all stationary processes.
For , let be the closed Euclidean ball. Ripley's K-function is
where is the full Palm distribution from The full Palm distribution defined by the refined Campbell identity and removes one distinguished occurrence at the origin. The Palm law has an origin occurrence almost surely by Existence and uniqueness of the full Palm law and the refined Campbell identity, and the reduced-measure identity The reduced second factorial moment measure is the Palm expectation after one-occurrence deletion gives the equivalent expression . For a simple process as defined in Random measures and locally finite point processes, deleting is the same as excluding the origin location; for a multiplicity-bearing process other co-located occurrences remain.
Axiom convention. AC and Countable Choice are inherited through the point-process and Palm dependency closure; no further choice is used by these definitions.
Depends on
- Stationarity, finite intensity, and spatial ergodicity
- Lebesgue measurable sets, the family $\mathcal{L}(\mathbb{R}^n)$, and the restricted set function $\lambda_n$
- A stationary point process of finite intensity has mean measure rho times Lebesgue measure
- The full Palm distribution defined by the refined Campbell identity
- Existence and uniqueness of the full Palm law and the refined Campbell identity
- Second factorial and reduced second factorial moment measures
- The reduced second factorial moment measure is the Palm expectation after one-occurrence deletion
- A sigma-finite signed measure that is absolutely continuous with respect to a sigma-finite positive measure has a unique almost-everywhere density
- The Axiom of Choice
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
Used by
- Border-corrected estimator for Ripley K Algorithm
- A finite window makes the border correction weight visible Example
- A translated lattice exposes recentering, atomic pair measures, and one-occurrence deletion Example
- A pair-correlation density integrates to Ripley K Theorem
- Ripley K for a homogeneous Poisson process is Euclidean ball volume Theorem
Dependency tree · two levels
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Sources
- Günter Last and Mathew Penrose, Lectures on the Poisson Process (2017 author-hosted version) (standard reference, not scraped)
- Adrian Baddeley, Spatial Point Processes and their Applications (standard reference, not scraped)