CRAN/E | DLSSM

DLSSM

Dynamic Logistic State Space Prediction Model

Installation

About

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.

Key Metrics

Version 0.1.0
R ≥ 3.10
Published 2022-12-13 493 days ago
Needs compilation? no
License GPL-3
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Maintainer

Maintainer

Jiakun Jiang

jiakunj@bnu.edu.cn

Authors

Jiakun Jiang

aut / cre

Wei Yang

aut

Wensheng Guo

aut

Material

Reference manual
Package source

Vignettes

DLSSM

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 3.10

Imports

Matrix

Suggests

knitr
rmarkdown
testthat ≥ 3.0.0
withr