Fixed Rank Kriging

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 manual

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0.1.8 by Andrew Zammit-Mangion, 2 months ago

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Authors: Andrew Zammit-Mangion [aut, cre], Timothy Davis [ctb], Patrick Amestoy [ctb], Iain Duff [ctb], John K. Reid [ctb]

Documentation:   PDF Manual  

Task views: Analysis of Spatial Data

GPL (>= 2) license

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

See at CRAN