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LatticeKrig  

Multi-Resolution Kriging Based on Markov Random Fields
View on CRAN: Click here


Download and install LatticeKrig package within the R console
Install from CRAN:
install.packages("LatticeKrig")

Install from Github:
library("remotes")
install_github("cran/LatticeKrig")

Install by package version:
library("remotes")
install_version("LatticeKrig", "9.3.0")



Attach the package and use:
library("LatticeKrig")
Maintained by
Douglas Nychka
[Scholar Profile | Author Map]
First Published: 2011-09-09
Latest Update: 2019-11-09
Description:
Methods for the interpolation of large spatial datasets. This package follows a "fixed rank Kriging" approach but provides a surface fitting method that can approximate standard spatial data models. Using a large number of basis functions allows for estimates that can come close to interpolating the observations (a spatial model with a small nugget variance.) Moreover, the covariance model for this method can approximate the Matern covariance family but also allows for a multi-resolution model and supports efficient computation of the profile likelihood for estimating covariance parameters. This is accomplished through compactly supported basis functions and a Markov random field model for the basis coefficients. These features lead to sparse matrices for the computations and this package makes of the R spam package for sparse linear algebra. An extension of this version over previous ones ( < 5.4 ) is the support for different geometries besides a rectangular domain. The Markov random field approach combined with a basis function representation makes the implementation of different geometries simple where only a few specific R functions need to be added with most of the computation and evaluation done by generic routines that have been tuned to be efficient. One benefit of this package's model/approach is the facility to do unconditional and conditional simulation of the field for large numbers of arbitrary points. There is also the flexibility for estimating non-stationary covariances and also the case when the observations are a linear combination (e.g. an integral) of the spatial process. Included are generic methods for prediction, standard errors for prediction, plotting of the estimated surface and conditional and unconditional simulation. See the 'LatticeKrig' GitHub repository for a vignette of this package. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research.
How to cite:
Douglas Nychka (2011). LatticeKrig: Multi-Resolution Kriging Based on Markov Random Fields. R package version 9.3.0, https://cran.r-project.org/web/packages/LatticeKrig. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.2.1 (2011-09-09 09:10), 1.4 (2012-02-10 17:36), 2.2.1 (2012-08-29 07:11), 2.4.3 (2013-04-16 07:43), 3.1 (2014-01-24 23:58), 3.3 (2014-07-11 06:47), 3.4 (2014-08-28 07:01), 5.4-1 (2015-11-05 08:31), 5.4 (2015-10-22 22:14), 5.5 (2016-05-22 09:20), 6.2 (2016-12-20 19:12), 6.4 (2017-05-23 05:39), 7.0 (2018-04-30 20:39), 8.4 (2019-11-09 16:40)
Other packages that cited LatticeKrig R package
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Other R packages that LatticeKrig depends, imports, suggests or enhances
Complete documentation for LatticeKrig
Functions, R codes and Examples using the LatticeKrig R package
Some associated functions: IcosohedronGrid . KrigingExampleData . LKDiag . LKDist . LKGeometry . LKRectangle . LKinfoCheck . LKrig.MLE . LKrig.basis . LKrig . LKrig.sim . LKrigDefaultFixedFunction . LKrigDistance-methods . LKrigInternal . LKrigLatticeCenters . LKrigMiscellaneous . LKrigNormalizeBasis . LKrigSAR . LKrigSetup . LKrigSetupAlpha . LKrigSetupAwght . LKrigSetupLattice . LatticeKrig . PeriodicGeometry . Radial.Basis . VignetteExamples . directionCosines . gridList-class . nonstationaryModels . registerdFORTRAN . setDefaultsLKinfo . 
Some associated R codes: Awght2Omega.R . GridList.R . LKDiag.R . LKDist.R . LKDistComponents.R . LKDistGrid.R . LKDistGridComponents.R . LKGridCheck.R . LKGridFindNmax.R . LKRectangleFastNormalization.R . LKSphere-Internal.R . LKinfoCheck.R . LKinfoUpdate.R . LKrig.MLE.R . LKrig.R . LKrig.basis.R . LKrig.coef.R . LKrig.cov.R . LKrig.cov.plot.R . LKrig.lnPlike.R . LKrig.make.par.grid.R . LKrig.misc.R . LKrig.precision.R . LKrig.quadraticform.R . LKrig.sim.R . LKrig.sim.conditional.R . LKrig.spind2spam.R . LKrig.traceA.R . LKrigCovWeightedObs.R . LKrigDefaultFixedFunction.R . LKrigDistance.R . LKrigFindLambda.R . LKrigFindLambdaAwght.R . LKrigLatticeCenters.R . LKrigLatticeScales.R . LKrigMakewU.R . LKrigMakewX.R . LKrigMarginalVariance.R . LKrigNormalizeBasis.R . LKrigSAR.R . LKrigSetup.R . LKrigSetupAlpha.R . LKrigSetupAwght.R . LKrigSetupAwghtObject.R . LKrigSetupLattice.R . LKrigUnrollGrid.R . LatticeKrig.R . LatticeKrigEasyDefaults.R . ModelBox.R . ModelCylinder.R . ModelInterval.R . ModelLKSphere.R . ModelRectangle.R . ModelRing.R . Radial.basis.R . Tensor.basis.R . WendlandFunction.R . convertIndexPeriodic.R . createLKrigObject.R . directionCosines.R . predict.LKrig.R . predictLKrigFixedFunction.R . predictSE.LKrig.R . predictSurface.LKrig.R . print.LKinfo.R . print.LKrig.R . print.LatticeKrig.R . setDefaultsLKinfo.R . summary.LKrig.R . surface.LKrig.R . triWeight.R . zzz.R .  Full LatticeKrig package functions and examples
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