Nothing
Provides a computationally efficient discrete approximation to logGaussian Cox process model for spatially aggregated disease count data. It uses Monte Carlo Maximum Likelihood for model parameter estimation as proposed by Christensen (2004) <doi: 10.1198/106186004X2525> and delivers prediction of spatially discrete and continuous relative risk. It performs inference for static spatial and spatiotemporal dataset.
Package details 


Author  Olatunji Johnson [aut, cre], Emanuele Giorgi [aut], Peter Diggle [aut] 
Maintainer  Olatunji Johnson <[email protected]> 
License  GPL2  GPL3 
Version  0.2.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.