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A flexible moving average algorithm for modeling drug exposure in pharmacoepidemiology studies as presented in the article: Ouchi, D., Giner-Soriano, M., Gómez-Lumbreras, A., Vedia Urgell, C.,Torres, F., & Morros, R. (2022). "Automatic Estimation of the Most Likely Drug Combination in Electronic Health Records Using the Smooth Algorithm : Development and Validation Study." JMIR medical informatics, 10(11), e37976. <doi:10.2196/37976>.
Version: | 1.0.0 |
Depends: | R (≥ 4.3) |
Imports: | dplyr, tidyr (≥ 1.3.0), zoo (≥ 1.8), stringr |
Suggests: | knitr, rmarkdown, ggplot2, gridExtra |
Published: | 2023-08-11 |
DOI: | 10.32614/CRAN.package.smoothy |
Author: | Dan Ouchi [aut, cre, cph], Alvaro Franquet [aut] |
Maintainer: | Dan Ouchi <dan.ouchi.vernet at gmail.com> |
License: | GPL (≥ 3) |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | smoothy results |
Reference manual: | smoothy.pdf |
Vignettes: |
introduction-to-smoothy |
Package source: | smoothy_1.0.0.tar.gz |
Windows binaries: | r-devel: smoothy_1.0.0.zip, r-release: smoothy_1.0.0.zip, r-oldrel: smoothy_1.0.0.zip |
macOS binaries: | r-release (arm64): smoothy_1.0.0.tgz, r-oldrel (arm64): smoothy_1.0.0.tgz, r-release (x86_64): smoothy_1.0.0.tgz, r-oldrel (x86_64): smoothy_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.