rsr: Ratio of RMSE to the standard deviation of the observations

Description

Ratio of the RMSE between simulated and observed values to the standard deviation of the observations.

Usage

rsr(sim, obs, ...)
## S3 method for class 'default':
rsr(sim, obs, na.rm=TRUE, ...)
## S3 method for class 'data.frame':
rsr(sim, obs, na.rm=TRUE, ...)
## S3 method for class 'matrix':
rsr(sim, obs, na.rm=TRUE, ...)

Arguments

sim

numeric, zoo, matrix or data.frame with simulated values

obs

numeric, zoo, matrix or data.frame with observed values

na.rm

a logical value indicating whether 'NA' should be stripped before the computation proceeds. When an 'NA' value is found at the i-th position in obs OR sim, the i-th value of obs AND sim ar

...

further arguments passed to or from other methods.

Value

Ratio of RMSE to the standard deviation of the observations. If sim and obs are matrixes, the returned value is a vector, with the RSR between each column of sim and obs.

References

Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., Veith, T.L. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE. 50(3):885-900

Examples

Run this code

sim <- 1:10
obs <- 1:10
rsr(sim, obs)

sim <- 2:11
obs <- 1:10
rsr(sim, obs)

##################
# Loading daily streamflows of the Ega River (Spain), from 1961 to 1970
require(zoo)
data(EgaEnEstellaQts)
obs <- EgaEnEstellaQts

# Generating a simulated daily time series, initially equal to the observed series
sim <- obs 

# Computing the 'rsr' for the "best" (unattainable) case
rsr(sim=sim, obs=obs)

# Randomly changing the first 2000 elements of 'sim', by using a normal distribution 
# with mean 10 and standard deviation equal to 1 (default of 'rnorm').
sim[1:2000] <- obs[1:2000] + rnorm(2000, mean=10)

# Computing the new 'rsr'
rsr(sim=sim, obs=obs)