Package: fdaSP 1.1.1

Mauro Bernardi

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

# Install 'fdaSP' in R:
install.packages('fdaSP', repos = c('https://cran.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

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

1.00 score 193 downloads 8 exports 20 dependencies

Last updated 1 years agofrom:95f90ec864. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKSep 29 2024
R-4.5-linux-x86_64OKSep 29 2024

Exports:confbandf2fSPf2fSP_cvf2sSPf2sSP_cvlmSPlmSP_cvsofthresh

Dependencies:codetoolsdoParallelFNNforeachiteratorskernlabKernSmoothkslatticeMatrixmclustmgcvmulticoolmvtnormnlmepracmarbibutilsRcppRcppArmadilloRdpack