biasCorrection: RAnEnExtra::biasCorrection
In Weiming-Hu/RAnEnExtra: Extra functions for RAnEn

Description Usage Arguments Author(s) References

RAnEnExtra::biasCorrection carries out a bias correction routine on the analog ensembles using a linear regression method. This correction method is useful for predicting extreme event.

biasCorrection(
  analogs,
  target.forecasts,
  historical.forecasts,
  similarity.time.index,
  similarity.station.index = NULL,
  regression.forecasts = NULL,
  regression.observations = NULL,
  forecast.id = NULL,
  activation.func = NULL,
  show.progress = T,
  return.more = F,
  group.func = mean,
  ...
)

`analogs`	A four-dimensional array for analog values with the dimensions `[stations, test times, lead times, members]`. This is usually generated from the `RAnEn::generateAnalogs`.
`target.forecasts`	A three- or four- dimensional array for test forecasts that analogs are generated for. The dimensions can either be `[stations, test times, lead times]` or `[stations, test times, lead times, 1]`. The forecasts should be aligned with the anlaogs for the first three dimensions.
`historical.forecasts`	The historical forecast search repository with the dimensions `[parameters, stations, times, lead times]`. This is usually the `Forecasts` used in `RAnEn::generateAnalogs`.
`similarity.time.index`	Similarity time index for each analog members. To have this for your analogs, you need to set `config$save_similarity_time_index = T` before you run `RAnEn::generateAnalogs`.
`similarity.station.index`	Similarity station index for each analog members. To have this for your analogs, you need to set `config$save_similarity_station_index = T` and use `SSE` for analog generation.
`regression.forecasts`	The forecast values used to calculate the slope of a linear regression line. These forecasts must correspond to observations for regression.
`regression.observations`	The observation values used to calculate the slope of a linear regression line These observations must correspond to forecasts for regression.
`forecast.id`	A forecasts parameter index used by the `historical.forecasts` to specify which forecast parameter to use.
`activation.func`	An activation function to signify whether a particular ensemble should be bias corrected. This function should takes a single argument and return a TRUE or FALSE. The single argument of the function will be an analog ensemble, or a numeric vector. For example, `activation.func = function(members) {if (mean(members) > 15) {return(T)} else {return(F)}}` will only correct ensembles that have an average over 15.
`show.progress`	Whether to show a progress bar
`return.more`	Whether to return more information
`group.func`	How to collapse the analog ensemble to a single value to calculate the amount of correction. In the paper and by default, this is `mean`.
`...`	Additional variables passed to `group.func`

Weiming Hu weiming@psu.edu

Martina Calovi mxc895@psu.edu

Alessandrini, Stefano, Simone Sperati, and Luca Delle Monache. "Improving the analog ensemble wind speed forecasts for rare events." Monthly Weather Review 147.7 (2019): 2677-2692.

Weiming-Hu/RAnEnExtra documentation built on Sept. 26, 2021, 6:44 a.m.