stpp-package: Space-Time Point Pattern simulation, visualisation and...

In stpp: Space-Time Point Pattern simulation, visualisation and analysis

Description

This package provides models of spatio-temporal point processes in a region S x T and statistical tools for analysing second-order properties of such processes. It also includes static and dynamic (2D and 3D) plots. stpp is the first dedicated unified computational environment in the area of spatio-temporal point processes.

The stpp package depends upon some other packages:

splancs: spatial and space-time point pattern analysis

rgl: interactive 3D plotting of densities and surfaces

rpanel: simple interactive controls for R using tcltk package

KernSmooth: functions for kernel smoothing for Wand & Jones (1995)

Details

stpp is a package for simulating, analysing and visualising patterns of points in space and time.

Following is a summary of the main functions and the dataset in the stpp package.

To visualise a spatio-temporal point pattern

• animation: space-time data animation.

• as.3dpoints: create data in spatio-temporal point format.

• plot.stpp: plot spatio-temporal point object. Either a two-panels plot showing spatial locations and cumulative times, or a one-panel plot showing spatial locations with times treated as a quantitative mark attached to each location.

• stan: 3D space-time animation.

To simulate spatio-temporal point patterns

• rinfec: simulate an infection point process,

• rinter: simulate an interaction (inhibition or contagious) point process,

• rlgcp: simulate a log-Gaussian Cox point process,

• rpcp: simulate a Poisson cluster point process,

• rpp: simulate a Poisson point process.

To analyse spatio-temporal point patterns

• PCFhat: space-time inhomogeneous pair correlation function,

• STIKhat: space-time inhomogeneous K-function.

Dataset

fmd: 2001 food-and-mouth epidemic in north Cumbria (UK).

Author(s)

Edith Gabriel <[e-mail]>, Barry Rowlingson and Peter J Diggle.

References

Baddeley A., Moller J. and Waagepetersen R. (2000). Non- and semi-parametric estimation of interaction in inhomogeneous point patterns. Statistica Neerlandica, 54, 329–350.

Chan, G. and Wood A. (1997). An algorithm for simulating stationary Gaussian random fields. Applied Statistics, Algorithm Section, 46, 171–181.

Chan, G. and Wood A. (1999). Simulation of stationary Gaussian vector fields. Statistics and Computing, 9, 265–268.

Diggle P. , Chedwynd A., Haggkvist R. and Morris S. (1995). Second-order analysis of space-time clustering. Statistical Methods in Medical Research, 4, 124–136.

Gabriel E., Diggle P. (2009) Second-order analysis of inhomogeneous spatio-temporal point process data. Statistica Neerlandica, 63, 43–51.

Gneiting T. (2002). Nonseparable, stationary covariance functions for space-time data. Journal of the American Statistical Association, 97, 590–600.

stpp documentation built on May 2, 2019, 4:50 p.m.