An R package for spatiotemporal prediction and forecasting for log-Gaussian Cox processes.
An object of class
logical of length 1.
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For examples and further details of the package, type vignette("lgcp"), or refer to the paper associated with this package.
The content of
lgcp can be broken up as follows:
Datasets wpopdata.rda, wtowncoords.rda, wtowns.rda. Giving regional and town poopulations as well as town coordinates,are provided by Wikipedia
and The Office for National Statistics under respectively
the Creative Commons Attribution-ShareAlike 3.0 Unported License and the Open Government Licence.
Model fitting and parameter estimation
Unconditional and conditional simulation
Summary statistics, diagnostics and visualisation
lgcp package depends upon some other important contributions to CRAN in order to operate; their uses here are indicated:
spatstat, sp, RandomFields, iterators, ncdf, methods, tcltk, rgl, rpanel, fields, rgdal, maptools, rgeos, raster
To see how to cite
citation("lgcp") at the console.
Benjamin Taylor, Health and Medicine, Lancaster University, Tilman Davies, Institute of Fundamental Sciences - Statistics, Massey University, New Zealand., Barry Rowlingson, Health and Medicine, Lancaster University Peter Diggle, Health and Medicine, Lancaster University
Brix A, Diggle PJ (2001). Spatiotemporal Prediction for log-Gaussian Cox processes. Journal of the Royal Statistical Society, Series B, 63(4), 823-841.
Diggle P, Rowlingson B, Su T (2005). Point Process Methodology for On-line Spatio-temporal Disease Surveillance. Environmetrics, 16(5), 423-434.
Wood ATA, Chan G (1994). Simulation of Stationary Gaussian Processes in [0,1]d. Journal of Computational and Graphical Statistics, 3(4), 409-432.
Moller J, Syversveen AR, Waagepetersen RP (1998). Log Gaussian Cox Processes. Scandinavian Journal of Statistics, 25(3), 451-482.
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