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 an example, see Grange et al. (2018) <doi:10.5194/acp-18-6223-2018>.
| Version: | 0.1.1 |
| Depends: | R (≥ 3.2.0) |
| Imports: | dplyr, ggplot2, lubridate, magrittr, pdp, purrr, ranger, stringr, strucchange, testthat, tibble, viridis |
| Suggests: | openair |
| Published: | 2018-05-08 |
| 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 |
| Materials: | README NEWS |
| CRAN checks: | rmweather results |
| Reference manual: | rmweather.pdf |
| Package source: | rmweather_0.1.1.tar.gz |
| Windows binaries: | r-devel: rmweather_0.1.1.zip, r-release: rmweather_0.1.1.zip, r-oldrel: rmweather_0.1.1.zip |
| OS X binaries: | r-release: not available, r-oldrel: not available |
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