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DLSSM  

Dynamic Logistic State Space Prediction Model
View on CRAN: Click here


Download and install DLSSM package within the R console
Install from CRAN:
install.packages("DLSSM")

Install from Github:
library("remotes")
install_github("cran/DLSSM")

Install by package version:
library("remotes")
install_version("DLSSM", "0.1.0")



Attach the package and use:
library("DLSSM")
Maintained by
Jiakun Jiang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-13
Latest Update: 2024-01-11
Description:
Implements the dynamic logistic state space model for binary outcome data proposed by Jiang et al. (2021) . 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.
How to cite:
Jiakun Jiang (2022). DLSSM: Dynamic Logistic State Space Prediction Model. R package version 0.1.0, https://cran.r-project.org/web/packages/DLSSM
Previous versions and publish date:
0.1.0 (2022-12-13 13:40)
Other packages that cited DLSSM R package
View DLSSM citation profile
Other R packages that DLSSM depends, imports, suggests or enhances
Functions, R codes and Examples using the DLSSM R package
Some associated functions: Batched . DLSSM.init . DLSSM . DLSSM.plot . DLSSM.valid . car.insur . 
Some associated R codes: DLSSM.R . data.R .  Full DLSSM package functions and examples
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