sparseFLMM: Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data

Estimation of functional linear mixed models for irregularly or sparsely sampled data based on functional principal component analysis.

Version:	0.4.1
Depends:	R (≥ 3.3), mgcv (≥ 1.8-12), refund (≥ 0.1-22)
Imports:	methods, parallel, MASS, Matrix, data.table
Published:	2021-06-19
Author:	Jona Cederbaum [aut, cre], Alexander Volkmann [aut], Almond Stöcker [aut]
Maintainer:	Jona Cederbaum <Jona.Cederbaum at gmail.com>
License:	GPL-2
NeedsCompilation:	no
Materials:	NEWS
In views:	FunctionalData
CRAN checks:	sparseFLMM results

Documentation:

Reference manual:

sparseFLMM.pdf

Downloads:

Package source:	sparseFLMM_0.4.1.tar.gz
Windows binaries:	r-devel: sparseFLMM_0.4.1.zip, r-release: sparseFLMM_0.4.1.zip, r-oldrel: sparseFLMM_0.4.1.zip
macOS binaries:	r-release (arm64): sparseFLMM_0.4.1.tgz, r-oldrel (arm64): sparseFLMM_0.4.1.tgz, r-release (x86_64): sparseFLMM_0.4.1.tgz, r-oldrel (x86_64): sparseFLMM_0.4.1.tgz
Old sources:	sparseFLMM archive

Reverse dependencies:

Reverse imports:

elastes, multifamm

Linking:

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