DGP4LCF
Dependent Gaussian Processes for Longitudinal Correlated Factors
Functionalities for analyzing high-dimensional and longitudinal biomarker data to facilitate precision medicine, using a joint model of Bayesian sparse factor analysis and dependent Gaussian processes. This paper illustrates the method in detail: J Cai, RJB Goudie, C Starr, BDM Tom (2023) <doi:10.48550/arXiv.2307.02781>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0.1 |
rolling linux/jammy R-4.5 | DGP4LCF_1.0.0.1.tar.gz |
1.0 MiB |
1.0.0.1 |
rolling linux/noble R-4.5 | DGP4LCF_1.0.0.1.tar.gz |
1.0 MiB |
1.0.0.1 |
rolling source/ R- | DGP4LCF_1.0.0.1.tar.gz |
601.6 KiB |
1.0.0.1 |
latest linux/jammy R-4.5 | DGP4LCF_1.0.0.1.tar.gz |
1.0 MiB |
1.0.0.1 |
latest linux/noble R-4.5 | DGP4LCF_1.0.0.1.tar.gz |
1.0 MiB |
1.0.0.1 |
latest source/ R- | DGP4LCF_1.0.0.1.tar.gz |
601.6 KiB |
1.0.0.1 |
2026-04-26 source/ R- | DGP4LCF_1.0.0.1.tar.gz |
601.6 KiB |
1.0.0.1 |
2026-04-23 source/ R- | DGP4LCF_1.0.0.1.tar.gz |
601.6 KiB |
1.0.0.1 |
2026-04-09 windows/windows R-4.5 | DGP4LCF_1.0.0.1.zip |
1.4 MiB |
1.0.0.1 |
2025-04-20 source/ R- | DGP4LCF_1.0.0.1.tar.gz |
601.6 KiB |