Package: fdaSP 1.1.1

fdaSP: Sparse Functional Data Analysis Methods

Provides algorithms to fit linear regression models under several popular penalization techniques and functional linear regression models based on Majorizing-Minimizing (MM) and Alternating Direction Method of Multipliers (ADMM) techniques. See Boyd et al (2010) <doi:10.1561/2200000016> for complete introduction to the method.

Authors:Mauro Bernardi [aut, cre], Marco Stefanucci [aut], Antonio Canale [ctb]

fdaSP_1.1.1.tar.gz
fdaSP_1.1.1.zip(r-4.5)fdaSP_1.1.1.zip(r-4.4)fdaSP_1.1.1.zip(r-4.3)
fdaSP_1.1.1.tgz(r-4.4-x86_64)fdaSP_1.1.1.tgz(r-4.4-arm64)fdaSP_1.1.1.tgz(r-4.3-x86_64)fdaSP_1.1.1.tgz(r-4.3-arm64)
fdaSP_1.1.1.tar.gz(r-4.5-noble)fdaSP_1.1.1.tar.gz(r-4.4-noble)
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fdaSP.pdf |fdaSP.html✨
fdaSP/json (API)

# Install 'fdaSP' in R:
install.packages('fdaSP', repos = c('https://maurobernardi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

8 exports 0.23 score 20 dependencies 180 downloads

Last updated 12 months agofrom:95f90ec864. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 31 2024
R-4.5-win-x86_64OKAug 31 2024
R-4.5-linux-x86_64OKAug 31 2024
R-4.4-win-x86_64OKAug 31 2024
R-4.4-mac-x86_64OKAug 31 2024
R-4.4-mac-aarch64OKAug 31 2024
R-4.3-win-x86_64OKAug 31 2024
R-4.3-mac-x86_64OKAug 31 2024
R-4.3-mac-aarch64OKAug 31 2024

Exports:confbandf2fSPf2fSP_cvf2sSPf2sSP_cvlmSPlmSP_cvsofthresh

Dependencies:codetoolsdoParallelFNNforeachiteratorskernlabKernSmoothkslatticeMatrixmclustmgcvmulticoolmvtnormnlmepracmarbibutilsRcppRcppArmadilloRdpack