Estimation, Variable Selection and Prediction for Functional Semiparametric Models
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 37includes a package overview page
- Examples that run
- 32%9 run in a plain check · 19 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 79%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 62%
Downloads
Dependencies
Installing fsemipar adds 37 packages (19 with compiled code, 30 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, isoband 1.5 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.1.1Latest
- 1.1.0
- RR 4.4.0 released · 2024-04-24
- 1.0.12024-02-21 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 1.02023-01-23
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-01-23
- Total releases
- 4 / 3 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 949 KB / 2 files
- Download size
- 1.0 MB
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