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Modelling Quality Indicator

mqi.Rd

Compute the Modelling Quality Indicator of observed and predicted data.

Usage

mqi(obs, pred, b = 2, alpha = 0.2, RV = 200, U_RV = 0.24, ...)

Arguments

obs

A numeric vector, data.frame or data.table of observed data.

pred

A numeric vector, data.frame or data.table of predicted (model) data.

b

An integer: in Fairmode it is arbitrarily set to 2. It determines the stringency of the Modelling Quality Objectice (MQO).

alpha

Non-proportional fraction factor (0 <= a <= 1) used to compute rmsu(). Default value for NO2 = 0.20.

RV

Reference value used to compute rmsu(). Default value for NO2 = 200.

U_RV

Standard measurement uncertainty around the RV, used to compute rmsu(). Default value for NO2 = 0.24.

...

Optional arguments passed to rmse().

Value

The Modelling Quality Indicator of input data as a numeric.

Details

The function computes the Modelling Quality Indicator (MQI) of observed and predicted data, according to the following definition: $$ \mathrm{MQI} = \frac{\mathrm{RMSE}(O, P)}{\beta \cdot \mathrm{RMS}_u(O)} $$

See rmsu documentation for further details.

The Modelling Quality Objective (MQO) is fulfilled when MQI <= 1.

Examples

if (FALSE) { # \dontrun{
# For NO2 data:
validationData[, .(mqi = mqi(obs, pred))]
} # }