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Open AccessJournal ArticleDOI

The Second-Order Analysis of Stationary Point Processes

Brian D. Ripley
- 01 Jun 1976 - 
- Vol. 13, Iss: 2, pp 255-266
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TLDR
In this paper, the authors provide a rigorous foundation for the second-order analysis of stationary point processes on general spaces, including the line and hyperplane processes of Davidson and Krickeberg.
Abstract
This paper provides a rigorous foundation for the second-order analysis of stationary point processes on general spaces. It illuminates the results of Bartlett on spatial point processes, and covers the point processes of stochastic geometry, including the line and hyperplane processes of Davidson and Krickeberg. The main tool is the decomposition of moment measures pioneered by Krickeberg and Vere-Jones. Finally some practical aspects of the analysis of point processes are discussed.

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Book

Stochastic Geometry for Wireless Networks

TL;DR: This rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects.
Journal ArticleDOI

spatstat: An R Package for Analyzing Spatial Point Patterns

TL;DR: This paper is a general description of spatstat and an introduction for new users.
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Spatial Analysis A Guide for Ecologists

TL;DR: In this paper, the authors present a spatial analysis of complete point location data, including points, lines, and graphs, and a multiscale analysis of the data set, including spatial diversity analysis and spatial autocorrelation.
References
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Book

The statistical analysis of series of events

David Cox, +1 more
TL;DR: This monograph is intended as a survey of some of the problems in theoretical statistics that stem from this sort of data, and has tried to give a simple description, with numerical examples, of the main methods that have been proposed.
Journal ArticleDOI

Neuronal Spike Trains and Stochastic Point Processes: II. Simultaneous Spike Trains

TL;DR: The statistical analysis of two simultaneously observed trains of neuronal spikes is described, using as a conceptual framework the theory of stochastic point processes, and the theory presented is illustrated by an application to experimentally obtained data from auditory neurons.
Journal ArticleDOI

A model for clustering

David J. Strauss
- 01 Aug 1975 -