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url: https://openair-project.github.io/deweather/
template:
package: openairpkgdown
navbar:
components:
casestudy:
text: Case Studies (External)
menu:
- text: (2019) Using meteorological normalisation to detect interventions in air quality time series
href: https://www.sciencedirect.com/science/article/pii/S004896971834244X
- text: (2012) A short-term intervention study — Impact of airport closure due to the eruption of Eyjafjallajökull on near-field air quality
href: https://www.sciencedirect.com/science/article/abs/pii/S1352231012001355
- text: (2009) Analysis of air pollution data at a mixed source location using boosted regression trees
href: https://www.sciencedirect.com/science/article/abs/pii/S1352231009003069
reference:
- title: Data
desc: >
Example datasets included with the package, used to demonstrate and test
deweathering functions.
contents: aqroadside
- title: Tune
desc: >
Tune hyperparameters for a deweathering model before it is fit. A 'best'
parameter set is automatically determined, but other functions are provided
to allow for closer interrogation so that these can be refined.
contents:
- tune_dw_model
- plot_tdw_tuning_metrics
- plot_tdw_testing_scatter
- title: Build
desc: >
Core functions for fitting deweathering models, used throughout the rest
of the `deweather` package for interpretation and prediction.
contents:
- build_dw_model
- finalise_tdw_model
- append_dw_vars
- title: Examine
desc: >
'getters' to extract specific features of a built `deweather` model or a
`deweather` 'tuning' object.
contents:
- get_dw_pollutant
- get_tdw_pollutant
- title: Visualise
desc: >
Functions for visualizing model components and relationships, including
variable importance and partial dependence plots.
contents:
- plot_dw_importance
- plot_dw_partial_1d
- plot_dw_partial_2d
- title: Predict
desc: >
Functions to apply a deweathering model for prediction.
contents:
- predict_dw
- simulate_dw_met
- plot_sim_trend