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deform (version 1.0.0)

Spatial Deformation and Dimension Expansion Gaussian Processes

Description

Methods for fitting nonstationary Gaussian process models by spatial deformation, as introduced by Sampson and Guttorp (1992) , and by dimension expansion, as introduced by Bornn et al. (2012) . Low-rank thin-plate regression splines, as developed in Wood, S.N. (2003) , are used to either transform co-ordinates or create new latent dimensions.

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Version

Install

install.packages('deform')

Monthly Downloads

156

Version

1.0.0

License

GPL-3

Maintainer

Ben Youngman

Last Published

October 19th, 2023

Functions in deform (1.0.0)

simulate.deform

Simulate from a fitted deform object
cencov

Correlation and covariance matrices from censored data
deform

Fitting low-rank nonstationary spatial Gaussian process models through spatial deformation
aniso

Fitting anisotropic spatial Gaussian process models
predict.deform

Predict from a fitted deform object
solar

Variance-covariance matrix for British Columbia solar radiation data
expand

Fitting low-rank nonstationary spatial Gaussian process models through dimension expansion
variogram

Plot the variogram for a fitted deform object
plot.deform

Plot a fitted deform object