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.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.5.0), grpreg |
| Imports: |
DiceKriging, splines, gtools, stats, parallelly, doParallel, parallel, foreach, ggplot2, gridExtra, tidyr |
| Published: |
2024-05-21 |
| DOI: |
10.32614/CRAN.package.fsemipar |
| Author: |
German Aneiros [aut],
Silvia Novo [aut, cre] |
| Maintainer: |
Silvia Novo <snovo at est-econ.uc3m.es> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
fsemipar results |
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