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Tools for fitting Bayesian Distributed Lag Models (DLMs) to longitudinal response data that is a count or binary. Count data is fit using negative binomial regression and binary is fit using quantile regression. The contribution of the lags are fit via b-splines. In addition, infers the predictor inclusion uncertainty. Multimomial models are not supported. Based on Dempsey and Wyse (2025) <doi:10.48550/arXiv.2403.03646>.
Version: | 1.0.0 |
Imports: | statmod, BayesLogit, dlnm, splines, dplyr, ggplot2, ggridges, reshape2 |
Published: | 2025-02-06 |
DOI: | 10.32614/CRAN.package.DiscreteDLM |
Author: | Daniel Dempsey |
Maintainer: | Daniel Dempsey <daniel.dempsey0 at gmail.com> |
BugReports: | https://github.com/DanDempsey/DiscreteDLM/issues |
License: | GPL-3 |
URL: | https://github.com/DanDempsey/DiscreteDLM |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | DiscreteDLM results |
Reference manual: | DiscreteDLM.pdf |
Package source: | DiscreteDLM_1.0.0.tar.gz |
Windows binaries: | r-devel: DiscreteDLM_1.0.0.zip, r-release: DiscreteDLM_1.0.0.zip, r-oldrel: DiscreteDLM_1.0.0.zip |
macOS binaries: | r-devel (arm64): DiscreteDLM_1.0.0.tgz, r-release (arm64): DiscreteDLM_1.0.0.tgz, r-oldrel (arm64): DiscreteDLM_1.0.0.tgz, r-devel (x86_64): DiscreteDLM_1.0.0.tgz, r-release (x86_64): DiscreteDLM_1.0.0.tgz, r-oldrel (x86_64): DiscreteDLM_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.