Package: DLSSM
Type: Package
Title: Dynamic Logistic State Space Prediction Model
Version: 1.1.1
Authors@R: c(
    person("Jiakun", "Jiang", email = "jiakunj@bnu.edu.cn", role = c("aut", "cre")),
    person("Wei", "Yang", email = "weiyang@pennmedicine.upenn.edu",role = "aut"),
    person("Wensheng","Guo", email = "wguo@pennmedicine.upenn.edu", role = "aut"))
Maintainer: Jiakun Jiang <jiakunj@bnu.edu.cn>
Description: 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.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.0
Imports: Matrix
Depends: R (>= 3.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Config/testthat/edition: 3
SystemRequirements: Intel MKL (optional for enhanced performance)
NeedsCompilation: no
Packaged: 2025-05-18 15:48:47 UTC; jiakun
Author: Jiakun Jiang [aut, cre],
  Wei Yang [aut],
  Wensheng Guo [aut]
Repository: CRAN
Date/Publication: 2025-05-22 05:10:16 UTC
Built: R 4.3.3; ; 2025-05-22 05:48:20 UTC; unix
