Index of Agreement
This function computes the Index of Agreement between sim and obs, with treatment of missing values.
If x is a matrix or a data frame, a vector of the Index of Agreement of the columns is returned.
d(sim, obs, ...) ## Default S3 method: d(sim, obs, na.rm=TRUE, ...) ## S3 method for class 'data.frame' d(sim, obs, na.rm=TRUE, ...) ## S3 method for class 'matrix' d(sim, obs, na.rm=TRUE, ...) ## S3 method for class 'zoo' d(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. |
d = 1 - [ ( sum( (obs - sim)^2 ) ] / sum( ( abs(sim - mean(obs)) + abs(obs - mean(obs)) )^2 )
The Index of Agreement (d) developed by Willmott (1981) as a standardized measure of the degree of model prediction error and varies between 0 and 1.
A value of 1 indicates a perfect match, and 0 indicates no agreement at all (Willmott, 1981).
The index of agreement can detect additive and proportional differences in the observed and simulated means and variances; however, it is overly sensitive to extreme values due to the squared differences (Legates and McCabe, 1999).
Index of agreement between sim and obs.
If sim and obs are matrixes, the returned value is a vector, with the index of agreement 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>
Willmott, C. J. 1981. On the validation of models. Physical Geography, 2, 184–194
Willmott, C. J. (1984). On the evaluation of model performance in physical geography. Spatial Statistics and Models, G. L. Gaile and C. J. Willmott, eds., 443-460
Willmott, C. J., S. G. Ackleson, R. E. Davis, J. J. Feddema, K. M. Klink, D. R. Legates, J. O'Donnell, and C. M. Rowe (1985), Statistics for the Evaluation and Comparison of Models, J. Geophys. Res., 90(C5), 8995-9005
Legates, D. R., and G. J. McCabe Jr. (1999), Evaluating the Use of "Goodness-of-Fit" Measures in Hydrologic and Hydroclimatic Model Validation, Water Resour. Res., 35(1), 233–241
obs <- 1:10 sim <- 1:10 d(sim, obs) obs <- 1:10 sim <- 2:11 d(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 index of agreement for the "best" (unattainable) case d(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 index of agreement d(sim=sim, obs=obs)
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