geographically optimal similarity

Computationally optimized function for geographically optimal similarity (GOS) model

Usage

gos(formula, data = NULL, newdata = NULL, kappa = 0.25, cores = 1)

formula: A formula of GOS model.
data: A data.frame or tibble of observation data.
newdata: A data.frame or tibble of prediction variables data.
kappa: A numeric value of the percentage of observation locations with high similarity to a prediction location. kappa = 1 - tau, where tau is the probability parameter in quantile operator. The default kappa is 0.25, meaning that 25% of observations with high similarity to a prediction location are used for modelling.
cores: positive integer(default is 1). If cores > 1, a 'parallel' package cluster with that many cores is created and used. You can also supply a cluster object.

A tibble made up of predictions and uncertainties.

Song, Y. (2022). Geographically Optimal Similarity. Mathematical Geosciences. doi: 10.1007/s11004-022-10036-8.

if (FALSE) {
data(zn)
data(grid)
g = gos(Zn ~ Slope + Water + NDVI  + SOC + pH + Road + Mine,
data = zn, newdata = grid, kappa = 0.08,cores = 6)
g
}