• Corpus ID: 203610413

Point Pattern Processes and Models

@article{Lomax2019PointPP,
  title={Point Pattern Processes and Models},
  author={Nik Lomax and Nick Malleson and Le Minh Kieu},
  journal={arXiv: Methodology},
  year={2019}
}
In recent years there has been a substantial increase in the availability of datasets which contain information about the location and timing of an event or group of events and the application of methods to analyse spatio-temporal datasets spans many disciplines. This chapter defines and provides an overview of tools for analysing spatial and temporal point patterns and processes, where discrete events occur at random across space or over time respectively. It also introduces the concept of… 

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References

SHOWING 1-10 OF 20 REFERENCES

stpp: An R Package for Plotting, Simulating and Analyzing Spatio-Temporal Point Patterns

This paper describes space-time point processes and introduces the package stpp to new users, the first dedicated unified computational environment in the area of spatio-temporal point processes.

Local Spatial Autocorrelation Statistics: Distributional Issues and an Application

The statistics Gi(d) and Gi*(d), introduced in Getis and Ord (1992) for the study of local pattern in spatial data, are extended and their properties further explored. In particular, nonbinary

Multidimensional Residual Analysis of Point Process Models for Earthquake Occurrences

Residual analysis methods for examining the fit of multidimensional point process models are applied to point process models for the space–time–magnitude distribution of earthquake occurrences,

The Analysis of Spatial Association by Use of Distance Statistics

Introduced in this paper is a family of statistics, G, that can be used as a measure of spatial association in a number of circumstances. The basic statistic is derived, its properties are

Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

This paper presents a meta-analysis of point processes and geostatistics using the K-function and goodness-of-fit testing to estimate second-order properties of spatio-temporal point patterns.

Simulation of Nonhomogeneous Poisson Processes by Thinning

Abstract : A simple and relatively efficient method for simulating one- dimensional and two-dimensional nonhomogeneous Poisson processes is presented. The method is applicable for any rate function

SEARCHING FOR LEUKAEMIA CLUSTERS USING A GEOGRAPHICAL ANALYSIS MACHINE

A Geographical Analysis Machine is built which simultaneously solves the problems of post hot: hypothesis testing, handling data errors, and the task of generating and evaluating hypotheses in an exploratory environment.

Spectra of some self-exciting and mutually exciting point processes

SUMMARY In recent years methods of data analysis for point processes have received some attention, for example, by Cox & Lewis (1966) and Lewis (1964). In particular Bartlett (1963a,b) has introduced

Stochastic collective model of public transport passenger arrival process

This study generalises the homogeneous Poisson process (HPP) to a more general non-HPP (NHPP) in which the arrival rate varies as a function of time, and proposes a new time-varying intensity function of the transit passenger arrival process.