View source: R/downscaleChunk.R
downscaleChunk | R Documentation |
Downscale climate data by splitting it in chunks, where there are as many chunks as latitudes.
This function encapsulates downscaleTrain
downscaleChunk(
x,
y,
newdata,
simulate = FALSE,
method,
...,
prepareData.args = list(global.vars = NULL, combined.only = TRUE, spatial.predictors
= NULL, local.predictors = NULL, extended.predictors = NULL),
condition = NULL,
threshold = NULL,
predict = TRUE,
path = getwd()
)
x |
The input grid (admits both single and multigrid, see |
y |
The observations dataset. It should be an object as returned by loadeR. |
newdata |
New datasets where to apply the model infered. It should be a list of objects as returned by loadeR, containing the new dataset/s. |
simulate |
A logic value indicating whether we want to simulate or not based on the GLM distributional parameters. Only relevant when perdicting with a GLM. Default to FALSE. |
method |
A string value. Type of transer function. Currently implemented options are |
... |
Optional parameters. These parameters are different depending on the method selected.
Every parameter has a default value set in the atomic functions in case that no selection is wanted.
Everything concerning these parameters is explained in the section |
prepareData.args |
A list with the arguments of the |
condition |
Inequality operator to be applied considering the given threshold.
|
threshold |
Numeric value. Threshold used as reference for the condition. Default is NULL. If a threshold value is supplied with no specification of the parameter |
predict |
A logic value. Should the prediction on the training set should be returned? Default is TRUE. |
path |
A string indicating the path where to save the prediction. |
Saves the prediction where specified.
J. Bano-Medina
downscaleTrain for training a downscaling model downscalePredict for prediction for a a test dataset with a trained model for downscaleR Wiki for downscaling seasonal forecasting and climate projections.
Other downscaling.functions:
downscaleCV()
,
downscalePredict()
,
downscaleTrain()
,
downscale()
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