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Collection of functions for fitting and interpreting distributed lag interaction models (DLIM). A DLIM regresses a scalar outcome on repeated measures of exposure and allows for modification by a continuous variable. Includes a dlim() function for fitting, predict() function for inference, and plotting functions for visualization. Details on methodology are described in Demateis et al. (2024) <doi:10.1002/env.2843>.
Version: | 0.1.0 |
Depends: | R (≥ 2.10) |
Imports: | dlnm, ggplot2, mgcv, reshape2, rlang, splines, tsModel, viridis |
Suggests: | rmarkdown, knitr |
Published: | 2024-02-29 |
DOI: | 10.32614/CRAN.package.dlim |
Author: | Danielle Demateis [aut, cre], Kayleigh Keller [aut], Ander Wilson [aut] |
Maintainer: | Danielle Demateis <Danielle.Demateis at colostate.edu> |
License: | GPL-3 |
NeedsCompilation: | no |
Citation: | dlim citation info |
Materials: | README |
CRAN checks: | dlim results |
Reference manual: | dlim.pdf |
Vignettes: |
dlimOverview |
Package source: | dlim_0.1.0.tar.gz |
Windows binaries: | r-devel: dlim_0.1.0.zip, r-release: dlim_0.1.0.zip, r-oldrel: dlim_0.1.0.zip |
macOS binaries: | r-release (arm64): dlim_0.1.0.tgz, r-oldrel (arm64): dlim_0.1.0.tgz, r-release (x86_64): dlim_0.1.0.tgz, r-oldrel (x86_64): dlim_0.1.0.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.