Fixed Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach, discussed in Cressie and Johannesson (2008), decomposes the field, and hence the covariance function, using a fixed set of n basis functions, where n is typically much smaller than the number of data points (or polygons) m. The method naturally allows for non-stationary, anisotropic covariance functions and the use of observations with varying support (with known error variance). The projected field is a key building block of the Spatial Random Effects (SRE) model, on which this package is based. The package FRK provides helper functions to model, fit, and predict using an SRE with relative ease. Reference: Cressie, N. and Johannesson, G. (2008) .

Documentation

Manual: FRK.pdf
Vignette: Spatial and spatio-temporal kriging with FRK

Maintainer: Andrew Zammit-Mangion <andrewzm at gmail.com>

Author(s): Andrew Zammit-Mangion*, Timothy Davis*, Patrick Amestoy*, Iain Duff*, John K. Reid*

Install package and any missing dependencies by running this line in your R console:

install.packages("FRK")

Depends R (>= 3.1)
Imports digest, dplyr, ggplot2, grDevices, Hmisc, Matrix, methods, plyr, Rcpp, sp, spacetime, stats, utils
Suggests covr, gstat, INLA, knitr, mapproj, parallel, rgeos, spdep, splancs, testthat, verification
Enhances dggrids
Linking to Rcpp
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Package FRK
Materials
URL
Task Views
Version 0.1.1
Published 2017-03-07
License GPL (>= 2.1)
BugReports http://github.com/andrewzm/FRK/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks FRK check results
Package source FRK_0.1.1.tar.gz