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This paper introduces an R package for spatio-temporal prediction andforecasting for log-Gaussian Cox processes. The main computational tool forthese models is Markov chain Monte Carlo and the new package, lgcp, thereforealso provides an extensible suite of functions for implementing MCMC algorithmsfor processes of this type. The modelling framework and details of inferentialprocedures are first presented before a tour of lgcp functionality is given viaa walk-through data-analysis. Topics covered include reading in and convertingdata, estimation of the key components and parameters of the model, specifyingoutput and simulation quantities, computation of Monte Carlo expectations,post-processing and simulation of data sets.

lgcp An R Package for Inference with Spatio-Temporal Log-Gaussian Cox Processes