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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-devel (arm64): DLSSM_1.1.0.tgz, r-release (arm64): DLSSM_1.1.0.tgz, r-oldrel (arm64): DLSSM_1.1.0.tgz, r-devel (x86_64): 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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These binaries (installable software) and packages are in development.
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