An R package for spatiotemporal prediction and forecasting for log-Gaussian Cox processes.
lgcpAn object of class logical of length 1.
The 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 lgcp, type citation("lgcp") at the console.
cruts cruts
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.
Data manipulation
Model fitting and parameter estimation
Unconditional and conditional simulation
Summary statistics, diagnostics and visualisation
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.