Measuring the Dependence between Two Point Processes through Confidence Intervals for the Second Order Distribution.

Abstract

To assess the dependence structure in a stationary bivariate point process the second-order distribution can be very useful. We prove that the natural estimates of this distribution, based on a realization A1 < A2 < ... < Asub A, B1 < B2 < ... < B sub b are asymptotically normal, and we present a method for constructing approximate confidence intervals for this distribution. Keywords: Bivariate point process; Ripley's K-function; cross-intensity function; Stationary point process; stationary sequence.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1987
Accession Number
ADA186735

Entities

People

  • Hani Doss

Organizations

  • Florida State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Data Analysis
  • Data Science
  • Equations
  • Gaussian Processes
  • Information Science
  • Intervals
  • Nanofibers
  • New York
  • Normality
  • Plastic Explosives
  • Probability
  • Random Variables
  • Stationary
  • Stationary Processes
  • Statistical Analysis
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.