VARMER (version 1.0.0)

fit.varmer: Training eta parameter for the varmer function

Description

Training eta parameter for the varmer function evaluating a vector of etas using Cross-validation. The best eta is the one yielding the highest KGE metric.

Usage

fit.varmer(
  stations.sf,
  v,
  etas = c(10, 100, 500, 1000, 5000),
  idw_formula = Variable ~ 1,
  factor_agg = 2,
  drty.out = tempdir(),
  apply_varmer = T
)

Arguments

stations.sf

data.frame with the observations metadata

v

grided image

etas

(optional) vector of eta values to evaluate in a CV exercise

idw_formula

formula for the idw interpolation

factor_agg

scalar which defines the aggregation factor to apply to the raster images in order to reduce computation requirements for solving varmer

drty.out

(optional) output folder for the CV metrics

apply_varmer

(optional) boolean which determines if a merging image is produced with the best eta