fdaconcur
Concurrent Regression and History Index Models for Functional Data
Provides an implementation of concurrent or varying coefficient regression methods for functional data. The implementations are done for both dense and sparsely observed functional data. Pointwise confidence bands can be constructed for each case. Further, the influence of past predictor values are modeled by a smooth history index function, while the effects on the response are described by smooth varying coefficient functions, which are very useful in analyzing real data such as COVID data. References: Yao, F., Müller, H.G., Wang, J.L. (2005) <doi:10.1214/009053605000000660>. Sentürk, D., Müller, H.G. (2010) <doi:10.1198/jasa.2010.tm09228>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.3 |
rolling source/ R- | fdaconcur_0.1.3.tar.gz |
33.4 KiB |
0.1.3 |
latest source/ R- | fdaconcur_0.1.3.tar.gz |
33.4 KiB |
0.1.3 |
2026-04-23 source/ R- | fdaconcur_0.1.3.tar.gz |
33.4 KiB |
0.1.3 |
2026-04-09 windows/windows R-4.5 | fdaconcur_0.1.3.zip |
485.9 KiB |