R: Efficiency Factor as Suggested by Nash and Sutcliffe

EF {qualV} | R Documentation

## Efficiency Factor as Suggested by Nash and Sutcliffe

### Description

The efficiency factor is a dimensionless statistic which directly relates predictions to observed data.

### Usage

    EF(o, p)

### Arguments

`o` | vector of observed values
`p` | vector of corresponding predicted values

### Details

Two time series are compared. `'EF'` is an overall measure of similarity between fitted and observed values. Any model giving a negative value cannot be recommended, whereas values close to one indicate a 'near-perfect' fit.

### Value

`EF` | efficiency factor

### References

Nash, J. E. and Sutcliffe, J. V. (1970) River flow forecasting through conceptual models part I - A discussion of principles. Journal of Hydrology, 10, 282-290.

Mayer, D. G. and Butler, D. G. (1993) Statistical Validation. Ecological Modelling, 68, 21-32.

### See Also

`MAE`, `MSE`, `MAPE`, `GRI`

### Examples

    # a constructed example
    x <- seq(0, 2*pi, 0.1)
    y <- 5 + sin(x)           # a process
    o <- y + rnorm(x, sd=0.2) # observation with random error
    p <- y + 0.1              # simulation with systematic bias

    plot(x, o); lines(x, p)
    EF(o, p)

    # observed and measured data with non-matching time intervals
    data(phyto)
    obsb <- na.omit(obs[match(sim$t, obs$t), ])
    simb <- sim[na.omit(match(obs$t, sim$t)), ]
    EF(obsb$y, simb$y)

[Package qualV version 0.3-3 Index]