Ratio of RMSE to the standard deviation of the observations
Ratio of the RMSE between simulated and observed values to the standard deviation of the observations.
rsr(sim, obs, ...) ## Default S3 method: 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, ...) ## S3 method for class 'zoo' rsr(sim, obs, na.rm=TRUE, ...)
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. |
... |
further arguments passed to or from other methods. |
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.
obs and sim has to have the same length/dimension
The missing values in obs and sim are removed before the computation proceeds, and only those positions with non-missing values in obs and sim are considered in the computation
Mauricio Zambrano Bigiarini <mzb.devel@gmail.com>
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
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 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)
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