KED: KED (Kriging with Extrenal Drift or Ordinary Kriging) using...

In AybarCL/Dorado: Easy Rainfall and Temperature Interpolation

Description

KED (Kriging with Extrenal Drift or Ordinary Kriging) using Raster and sp Objects

Usage

KED(gauge, cov, formula, model, crossval = F, ...)

Arguments

gauge	Is an object of SpatialPointsDataFrame-class.
cov	Is an object of RasterLayer.
formula	that defines the dependent variable as a linear model
model	variogram model of dependent variable (or its residuals), defined by a call to FitVariogram
crossval	logical, Generate crosvalidation of independent variables; suppose the dependent variable has name 'z', for Kriging with Extrenal Drift (KED) use the formula 'z~x+y+....', you do not need define
...	parameters that are passed on to variogram variogram when calculating the sample variogram

Value

a List that contains: Interpol is the KED result in Raster, params being residual that are spatial residual obtains in the cross-validation (residual), MSE is the Residual Mean squared error and finally var is the variogram model.

Author(s)

Cesar Aybar <[e-mail]>

See Also

krige autoKrige

Examples

library(raster)
library(Dorado)
data("Dorado")
gauge <- mean_doble_Station(gauge = Dorado$gauge,cov = Dorado$TRMM)
sat <- Dorado$TRMM
x <- KED(gauge = gauge,cov = sat,formula = PP_anual~Precipitacion_Anual,crossval = TRUE)

AybarCL/Dorado documentation built on Jan. 13, 2020, 1:13 p.m.