Package: fcr 1.0
fcr: Functional Concurrent Regression for Sparse Data
Dynamic prediction in functional concurrent regression with an application to child growth. Extends the pffr() function from the 'refund' package to handle the scenario where the functional response and concurrently measured functional predictor are irregularly measured. Leroux et al. (2017), Statistics in Medicine, <doi:10.1002/sim.7582>.
Authors:
fcr_1.0.tar.gz
fcr_1.0.zip(r-4.5)fcr_1.0.zip(r-4.4)fcr_1.0.zip(r-4.3)
fcr_1.0.tgz(r-4.4-any)fcr_1.0.tgz(r-4.3-any)
fcr_1.0.tar.gz(r-4.5-noble)fcr_1.0.tar.gz(r-4.4-noble)
fcr_1.0.tgz(r-4.4-emscripten)fcr_1.0.tgz(r-4.3-emscripten)
fcr.pdf |fcr.html✨
fcr/json (API)
| # Install 'fcr' in R: |
| install.packages('fcr', repos = c('https://andrew-leroux.r-universe.dev', 'https://cloud.r-project.org')) |
- content - Example dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:98d8dcd75e. Checks:OK: 3 NOTE: 4. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 14 2024 |
| R-4.5-win | NOTE | Sep 14 2024 |
| R-4.5-linux | NOTE | Sep 14 2024 |
| R-4.4-win | NOTE | Sep 14 2024 |
| R-4.4-mac | NOTE | Sep 14 2024 |
| R-4.3-win | OK | Sep 14 2024 |
| R-4.3-mac | OK | Sep 14 2024 |
Exports:fcr
Dependencies:dotCall64facefieldslatticemapsMatrixmatrixcalcmgcvnlmeRcppspamviridisLite
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Dynamic prediction in functional concurrent regression with sparse functional covariates | fcr-package dynfcr |
| Example dataset | content |
| Fit Functional Concurrent Regression | fcr |
| Plotting an fcr model fit | plot.fcr |
| Prediction for fcr | predict.fcr |
