md: Modified index of agreement

View source: R/md.R

mdR Documentation

Modified index of agreement

Description

This function computes the modified 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 modified index of agreement among the columns is returned.

Usage

md(sim, obs, ...)

## Default S3 method:
md(sim, obs, j=1, na.rm=TRUE, fun=NULL, ...,
            epsilon.type=c("none", "Pushpalatha2012", "otherFactor", "otherValue"), 
            epsilon.value=NA)

## S3 method for class 'data.frame'
md(sim, obs, j=1, na.rm=TRUE, fun=NULL, ...,
            epsilon.type=c("none", "Pushpalatha2012", "otherFactor", "otherValue"), 
            epsilon.value=NA)

## S3 method for class 'matrix'
md(sim, obs, j=1, na.rm=TRUE, fun=NULL, ...,
            epsilon.type=c("none", "Pushpalatha2012", "otherFactor", "otherValue"), 
            epsilon.value=NA)

## S3 method for class 'zoo'
md(sim, obs, j=1, na.rm=TRUE, fun=NULL, ...,
            epsilon.type=c("none", "Pushpalatha2012", "otherFactor", "otherValue"), 
            epsilon.value=NA)

Arguments

sim

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

obs

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

j

numeric, with the exponent to be used in the computation of the modified index of agreement. The default value is j=1.

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 are removed before the computation.

fun

function to be applied to sim and obs in order to obtain transformed values thereof before computing the modified index of agreement.

The first argument MUST BE a numeric vector with any name (e.g., x), and additional arguments are passed using ....

...

arguments passed to fun, in addition to the mandatory first numeric vector.

epsilon.type

argument used to define a numeric value to be added to both sim and obs before applying fun.

It is was designed to allow the use of logarithm and other similar functions that do not work with zero values.

Valid values of epsilon.type are:

1) "none": sim and obs are used by fun without the addition of any nummeric value.

2) "Pushpalatha2012": one hundredth (1/100) of the mean observed values is added to both sim and obs before applying fun, as described in Pushpalatha et al. (2012).

3) "otherFactor": the numeric value defined in the epsilon.value argument is used to multiply the the mean observed values, instead of the one hundredth (1/100) described in Pushpalatha et al. (2012). The resulting value is then added to both sim and obs, before applying fun.

4) "otherValue": the numeric value defined in the epsilon.value argument is directly added to both sim and obs, before applying fun.

epsilon.value

numeric value to be added to both sim and obs when epsilon.type="otherValue".

Details

md = 1 - \frac{ \sum_{i=1}^N {\left| O_i - S_i \right| ^j} } { \sum_{i=1}^N { \left| S_i - \bar{O} \right| + \left| O_i - \bar{O} \right|^j } }

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).

Value

Modified index of agreement between sim and obs.

If sim and obs are matrixes, the returned value is a vector, with the modified index of agreement between each column of sim and obs.

Note

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

Author(s)

Mauricio Zambrano Bigiarini <mzb.devel@gmail.com>

References

Krause, P., Boyle, D. P., and Base, F.: Comparison of different efficiency criteria for hydrological model assessment, Adv. Geosci., 5, 89-97, 2005

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

See Also

d, dr, rd, gof, ggof

Examples

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

obs <- 1:10
sim <- 2:11
md(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 modified index of agreement for the "best" (unattainable) case
md(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 'd1'
md(sim=sim, obs=obs)

hzambran/hydroGOF documentation built on March 27, 2024, 11:21 p.m.