svcm: 2d and 3d Space-Varying Coefficient Models

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2d and 3d space-varying coefficient models are fitted to regular grid data using either a full B-spline tensor product approach or a sequential approximation. The latter one is computationally more efficient. Resolution increment is enabled.

Author
Susanne Heim, with support from Paul Eilers, Thomas Kneib, and Michael Kobl
Date of publication
2009-06-14 19:13:12
Maintainer
Susanne Heim <susanneheim@gmx.net>
License
GPL (>= 2)
Version
0.1.2
URLs

View on CRAN

Man pages

brain2d
Two-dimensional Diffusion Weighted Dataset
brain3d
Three-dimensional Diffusion Weighted Dataset
cleversearch
Optimization over a parameter grid
resolution
Re-scaling resolution of SVCM predictors and effects
svcm
Fitting space-varying coefficient models
svcm-package
2d and 3d Space-Varying Coefficient Models

Files in this package

svcm
svcm/MD5
svcm/TODO
svcm/tests
svcm/tests/svcm3d.R
svcm/src
svcm/src/dsC2env.c
svcm/src/combi.cpp
svcm/R
svcm/R/targetsvcm.R
svcm/R/svcm.R
svcm/R/SEQpsi.R
svcm/R/resolution.R
svcm/R/predictsvcm.R
svcm/R/EDofTP.R
svcm/R/dsC2env.R
svcm/R/cleversearch.R
svcm/R/calknots.R
svcm/NAMESPACE
svcm/man
svcm/man/svcm.Rd
svcm/man/svcm-package.Rd
svcm/man/resolution.Rd
svcm/man/cleversearch.Rd
svcm/man/brain3d.Rd
svcm/man/brain2d.Rd
svcm/inst
svcm/inst/doc
svcm/inst/doc/svcm_resol_2dexample.pdf
svcm/inst/doc/svcm_3dexample.pdf
svcm/inst/doc/svcm_2dexample.pdf
svcm/inst/doc/svcm.pdf
svcm/inst/doc/resolution_scheme.pdf
svcm/inst/doc/data_3dexample.pdf
svcm/inst/CITATION
svcm/DESCRIPTION
svcm/data
svcm/data/brain3d.rda
svcm/data/brain2d.rda
svcm/COPYING