glimpr: GLM downscaling

In SantanderMetGroup/downscaleR: A climate4R package for statistical downscaling <http://meteo.unican.es/climate4r>

GLM downscaling

Description

Implementation of GLM's to downscale precipitation data

Usage

glimpr(
  y = y,
  modelPars = modelPars,
  simulate = c("none", "loocv", "kfold"),
  return.models = FALSE,
  wet.threshold = wet.threshold,
  n.pcs = n.pcs
)

Arguments

y	A grid or station data containing the observed climate data for the training period
modelPars	Output object from function ppModelSetup containing the predictors and test data
simulate	Character. Options are "no", "yes" or "occurrence". The last option simulates the occurrence but not the amount.
wet.threshold	Value below which precipitation amount is considered zero
n.eofs	Integer indicating the number of EOFs to be used as predictors

Author(s)

J Bedia, M Iturbide

See Also

Other downscaling: biasCorrection(), isimip()

SantanderMetGroup/downscaleR documentation built on July 4, 2023, 4:28 a.m.