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>.
| Version: |
1.0 |
| Depends: |
R (≥ 3.2.4), face (≥ 0.1), mgcv (≥ 1.7), fields (≥ 9.0) |
| Suggests: |
knitr, rmarkdown |
| Published: |
2018-03-13 |
| DOI: |
10.32614/CRAN.package.fcr |
| Author: |
Andrew Leroux [aut, cre],
Luo Xiao [aut, cre],
Ciprian Crainiceanu [aut],
William Checkly [aut] |
| Maintainer: |
Andrew Leroux <aleroux2 at jhu.edu> |
| License: |
GPL (≥ 3) |
| NeedsCompilation: |
no |
| CRAN checks: |
fcr results |
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