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
DOI: 10.32614/CRAN.package.sparseFLMM
Author: Jona Cederbaum [aut, cre], Alexander Volkmann [aut], Almond Stöcker [aut]
Maintainer: Jona Cederbaum <Jona.Cederbaum at>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
In views: FunctionalData
CRAN checks: sparseFLMM results


Reference manual: sparseFLMM.pdf


Package source: sparseFLMM_0.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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 depends: randnet
Reverse imports: elastes, MJMbamlss, multifamm


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