amber (version 1.0.3)

intFun.rmse: Root mean square error (RMSE)

Description

This function computes the root mean square error (RMSE), which is defined as:

\($rmse(\lambda, \phi)=\sqrt{\frac{1}{t_{f}-t_{0}}\int_{t_{0}}^{t_{f}}(v_{mod}(t,\lambda, \phi)-v_{ref}(t,\lambda, \phi))^{2}dt}$\)

where \(\lambda\) is the longitude, \(\phi\) is the latitude, \(t\) is the time, \(t_0\) is the initial time step, \(t_f\) is the final time time step, \(v_{mod}\) is a modelled variable and \(v_{ref}\) is the corresponding reference variable.

Usage

intFun.rmse(mod, ref)

Arguments

mod

An R object (model output data)

ref

An R object (reference data)

Value

An R object that gives the root mean square error when comparing mod against ref.

Examples

# NOT RUN {
library(raster)
# create two raster stacks
for(i in 1:100)
{
 mod <- raster::raster(matrix(runif(100,-1,1), ncol=10))
 ref <- raster::raster(matrix(runif(100,-2,2), ncol=10))
 assign(paste('mod', i , sep='_'), mod)
 assign(paste('ref', i , sep='_'), ref)
}
my.list.mod <- lapply(ls(pattern='mod_'), get)
my.list.ref <- lapply(ls(pattern='ref_'), get)
mod <- do.call(stack, my.list.mod)
ref <- do.call(stack, my.list.ref)
# compute RMSE
rmse <- intFun.rmse(mod,ref)
plot(rmse); text(rmse, digits=2)

# }