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Implements the dynamic logistic state space model for binary outcome data proposed by Jiang et al. (2021) <doi:10.1111/biom.13593>. It provides a computationally efficient way to update the prediction whenever new data becomes available. It allows for both time-varying and time-invariant coefficients, and use cubic smoothing splines to model varying coefficients. The smoothing parameters are objectively chosen by maximum likelihood. The model is updated using batch data accumulated at pre-specified time intervals.
| Version: | 1.1.0 |
| Depends: | R (≥ 3.10) |
| Imports: | Matrix |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), withr |
| Published: | 2025-03-17 |
| DOI: | 10.32614/CRAN.package.DLSSM |
| Author: | Jiakun Jiang [aut, cre], Wei Yang [aut], Wensheng Guo [aut] |
| Maintainer: | Jiakun Jiang <jiakunj at bnu.edu.cn> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | DLSSM results |
| Reference manual: | DLSSM.pdf |
| Vignettes: |
DLSSM (source, R code) |
| Package source: | DLSSM_1.1.0.tar.gz |
| Windows binaries: | r-devel: DLSSM_1.1.0.zip, r-release: DLSSM_1.1.0.zip, r-oldrel: DLSSM_1.1.0.zip |
| macOS binaries: | r-release (arm64): DLSSM_1.1.0.tgz, r-oldrel (arm64): DLSSM_1.1.0.tgz, r-release (x86_64): DLSSM_1.1.0.tgz, r-oldrel (x86_64): DLSSM_1.1.0.tgz |
| Old sources: | DLSSM archive |
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