Package: fsemipar 1.1.1

Silvia Novo

fsemipar: Estimation, Variable Selection and Prediction for Functional Semiparametric Models

Routines for the estimation or simultaneous estimation and variable selection in several functional semiparametric models with scalar responses are provided. These models include the functional single-index model, the semi-functional partial linear model, and the semi-functional partial linear single-index model. Additionally, the package offers algorithms for handling scalar covariates with linear effects that originate from the discretization of a curve. This functionality is applicable in the context of the linear model, the multi-functional partial linear model, and the multi-functional partial linear single-index model.

Authors:German Aneiros [aut], Silvia Novo [aut, cre]

fsemipar_1.1.1.tar.gz
fsemipar_1.1.1.tar.gz(r-4.5-noble)fsemipar_1.1.1.tar.gz(r-4.4-noble)
fsemipar_1.1.1.tgz(r-4.4-emscripten)fsemipar_1.1.1.tgz(r-4.3-emscripten)
fsemipar.pdf |fsemipar.html✨
fsemipar/json (API)

# Install 'fsemipar' in R:
install.packages('fsemipar', repos = 'https://cloud.r-project.org')
Datasets:

On CRAN:

Conda:

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

1.30 score 180 downloads 76 exports 45 dependencies

Last updated 11 months agofrom:080e003a1e. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 31 2025
R-4.5-linuxOKMar 31 2025
R-4.4-linuxOKMar 31 2025

Exports:FASSMR.kernel.fitFASSMR.kNN.fitfsim.kernel.fitfsim.kernel.fit.optimfsim.kernel.testfsim.kNN.fitfsim.kNN.fit.optimfsim.kNN.testIASSMR.kernel.fitIASSMR.kNN.fitlm.pels.fitplot.FASSMR.kernelplot.FASSMR.kNNplot.fsim.kernelplot.fsim.kNNplot.IASSMR.kernelplot.IASSMR.kNNplot.lm.pelsplot.PVSplot.PVS.kernelplot.PVS.kNNplot.sfpl.kernelplot.sfpl.kNNplot.sfplsim.kernelplot.sfplsim.kNNpredict.FASSMR.kernelpredict.FASSMR.kNNpredict.fsim.kernelpredict.fsim.kNNpredict.IASSMR.kernelpredict.IASSMR.kNNpredict.lm.pelspredict.PVSpredict.PVS.kernelpredict.PVS.kNNpredict.sfpl.kernelpredict.sfpl.kNNpredict.sfplsim.kernelpredict.sfplsim.kNNprint.FASSMR.kernelprint.FASSMR.kNNprint.fsim.kernelprint.fsim.kNNprint.IASSMR.kernelprint.IASSMR.kNNprint.lm.pelsprint.PVSprint.PVS.kernelprint.PVS.kNNprint.sfpl.kernelprint.sfpl.kNNprint.sfplsim.kernelprint.sfplsim.kNNprojecPVS.fitPVS.kernel.fitPVS.kNN.fitsemimetric.projecsfpl.kernel.fitsfpl.kNN.fitsfplsim.kernel.fitsfplsim.kNN.fitsummary.FASSMR.kernelsummary.FASSMR.kNNsummary.fsim.kernelsummary.fsim.kNNsummary.IASSMR.kernelsummary.IASSMR.kNNsummary.lm.pelssummary.PVSsummary.PVS.kernelsummary.PVS.kNNsummary.sfpl.kernelsummary.sfpl.kNNsummary.sfplsim.kernelsummary.sfplsim.kNN

Dependencies:clicodetoolscolorspacecpp11DiceKrigingdoParalleldplyrfansifarverforeachgenericsggplot2gluegridExtragrpreggtablegtoolsisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeparallellypillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Citation

To cite package ‘fsemipar’ in publications use:

Aneiros G, Novo S (2024). fsemipar: Estimation, Variable Selection and Prediction for Functional Semiparametric Models. R package version 1.1.1, https://CRAN.R-project.org/package=fsemipar.

Corresponding BibTeX entry: 

  @Manual{,
    title = {fsemipar: Estimation, Variable Selection and Prediction
      for Functional Semiparametric Models},
    author = {German Aneiros and Silvia Novo},
    year = {2024},
    note = {R package version 1.1.1},
    url = {https://CRAN.R-project.org/package=fsemipar},
  }

Readme and manuals

Help Manual

Help pageTopics
Estimation, Variable Selection and Prediction for Functional Semiparametric Modelsfsemipar-package fsemipar
Impact point selection with FASSMR and kernel estimationFASSMR.kernel.fit
Impact point selection with FASSMR and kNN estimationFASSMR.kNN.fit
Package fsemipar internal functionsfsemipar.internal
Functional single-index model fit using kernel estimation and joint LOOCV minimisationfsim.kernel.fit
Functional single-index model fit using kernel estimation and iterative LOOCV minimisationfsim.kernel.fit.optim
Functional single-index kernel predictorfsim.kernel.test
Functional single-index model fit using kNN estimation and joint LOOCV minimisationfsim.kNN.fit
Functional single-index model fit using kNN estimation and iterative LOOCV minimisationfsim.kNN.fit.optim
Functional single-index kNN predictorfsim.kNN.test
Impact point selection with IASSMR and kernel estimationIASSMR.kernel.fit
Impact point selection with IASSMR and kNN estimationIASSMR.kNN.fit
Regularised fit of sparse linear regressionlm.pels.fit
Graphical representation of regression model outputsplot.FASSMR.kernel plot.FASSMR.kNN plot.fsim.kernel plot.fsim.kNN plot.IASSMR.kernel plot.IASSMR.kNN plot.lm.pels plot.PVS plot.PVS.kernel plot.PVS.kNN plot.sfpl.kernel plot.sfpl.kNN plot.sfplsim.kernel plot.sfplsim.kNN
Prediction for FSIMpredict.fsim.kernel predict.fsim.kNN
Prediction for MFPLSIMpredict.IASSMR.kernel predict.IASSMR.kNN
Prediction for linear modelspredict.lm.pels predict.PVS
Prediction for MFPLMpredict.PVS.kernel predict.PVS.kNN
Predictions for SFPLMpredict.sfpl.kernel predict.sfpl.kNN
Prediction for SFPLSIM and MFPLSIM (using FASSMR)predict.FASSMR.kernel predict.FASSMR.kNN predict.sfplsim.kernel predict.sfplsim.kNN
Summarise information from FSIM estimationprint.fsim.kernel print.fsim.kNN summary.fsim.kernel summary.fsim.kNN
Summarise information from linear models estimationprint.lm.pels print.PVS summary.lm.pels summary.PVS
Summarise information from MFPLM estimationprint.PVS.kernel print.PVS.kNN summary.PVS.kernel summary.PVS.kNN
Summarise information from MFPLSIM estimationprint.FASSMR.kernel print.FASSMR.kNN print.IASSMR.kernel print.IASSMR.kNN summary.FASSMR.kernel summary.FASSMR.kNN summary.IASSMR.kernel summary.IASSMR.kNN
Summarise information from SFPLM estimationprint.sfpl.kernel print.sfpl.kNN summary.sfpl.kernel summary.sfpl.kNN
Summarise information from SFPLSIM estimationprint.sfplsim.kernel print.sfplsim.kNN summary.sfplsim.kernel summary.sfplsim.kNN
Inner product computationprojec
Impact point selection with PVSPVS.fit
Impact point selection with PVS and kernel estimationPVS.kernel.fit
Impact point selection with PVS and kNN estimationPVS.kNN.fit
Projection semi-metric computationsemimetric.projec
SFPLM regularised fit using kernel estimationsfpl.kernel.fit
SFPLM regularised fit using kNN estimationsfpl.kNN.fit
SFPLSIM regularised fit using kernel estimationsfplsim.kernel.fit
SFPLSIM regularised fit using kNN estimationsfplsim.kNN.fit
Sugar dataSugar
Tecator dataTecator