rmweather: Tools to Conduct Meteorological Normalisation on Air Quality
Data
An integrated set of tools to allow data users to conduct
meteorological normalisation on air quality data. This meteorological
normalisation technique uses predictive random forest models to remove
variation of pollutant concentrations so trends and interventions can be
explored in a robust way. For examples, see Grange et al. (2018)
<doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019)
<doi:10.1016/j.scitotenv.2018.10.344>.
| Version: |
0.1.51 |
| Depends: |
R (≥ 3.2.0) |
| Imports: |
dplyr, ggplot2, lubridate, magrittr, pdp, purrr, ranger, stringr, strucchange, tibble, viridis |
| Suggests: |
testthat, openair |
| Published: |
2020-06-15 |
| Author: |
Stuart K. Grange 
[cre, aut] |
| Maintainer: |
Stuart K. Grange <stuart.grange at york.ac.uk> |
| BugReports: |
https://github.com/skgrange/rmweather/issues |
| License: |
GPL-3 | file LICENSE |
| URL: |
https://github.com/skgrange/rmweather |
| NeedsCompilation: |
no |
| Citation: |
rmweather citation info |
| Materials: |
README NEWS |
| CRAN checks: |
rmweather results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=rmweather
to link to this page.