Fixed Rank Kriging is a tool for spatial/spatiotemporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of r basis functions, where r is typically much smaller than the number of data points (or polygons) m. This lowrank basisfunction representation facilitates the modelling of 'big' spatial/spatiotemporal data. The method naturally allows for nonstationary, anisotropic covariance functions. Discretisation of the spatial domain into socalled basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both pointreferenced and areal supports, potentially simultaneously), and prediction over arbitrary userspecified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above of the package `FRK` also supports modelling of nonGaussian data, by employing a spatial generalised linear mixed model (GLMM) framework to cater for Poisson, binomial, negativebinomial, gamma, and inverseGaussian distributions. ZammitMangion and Cressie <doi:10.18637/jss.v098.i04> describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs.
Package details 


Author  Andrew ZammitMangion [aut, cre], Matthew SainsburyDale [aut] 
Maintainer  Andrew ZammitMangion <andrewzm@gmail.com> 
License  GPL (>= 2) 
Version  2.0.0 
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.