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Downscales a raster to a higher resolution raster using a robust regression
raster.downscale(
x,
y,
p = NULL,
n = NULL,
filename = FALSE,
scatter = FALSE,
...
)
Raster class object representing independent variable(s)
Raster class object representing dependent variable
Percent sample size
Fixed sample size
Name of output raster
(FALSE/TRUE) Optional scatter plot
Additional arguments passed to predict
A list object containing:
downscale downscaled raster (omitted if filename is defined)
model rlm model object
MSE Mean Square Error
AIC Akaike information criterion
# NOT RUN {
library(raster)
elev <- raster::getData('alt', country='SWZ', mask=TRUE)
tmax <- raster::getData('worldclim', var='tmax', res=10,
lon=8.25, lat=46.8)
tmax <- crop(tmax[[1]], extent(elev))
# Downscale temperature
tmax.ds <- raster.downscale(elev, tmax, scatter=TRUE)
opar <- par(no.readonly=TRUE)
par(mfrow=c(2,2))
plot(tmax, main="Temp max")
plot(elev, main="elevation")
plot(tmax.ds$downscale, main="Downscaled Temp max")
par(opar)
# }
# NOT RUN {
# }
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