View source: R/ErrorCrit_RMSE.R
ErrorCrit_RMSE | R Documentation |
Function which computes an error criterion based on the root-mean-square error (RMSE).
ErrorCrit_RMSE(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE)
InputsCrit |
[object of class InputsCrit] see |
OutputsModel |
[object of class OutputsModel] see |
warnings |
(optional) [boolean] boolean indicating if the warning messages are shown, default = |
verbose |
(optional) [boolean] boolean indicating if the function is run in verbose mode or not, default = |
In addition to the criterion value, the function outputs include a multiplier (-1 or +1) which allows
the use of the function for model calibration: the product CritValue \times Multiplier
is the criterion to be minimised
(Multiplier = +1 for RMSE).
[list] list containing the function outputs organised as follows:
$CritValue | [numeric] value of the criterion |
$CritName | [character] name of the criterion |
$CritBestValue | [numeric] theoretical best criterion value |
$Multiplier | [numeric] integer indicating whether the criterion is indeed an error (+1) or an efficiency (-1) |
$Ind_notcomputed | [numeric] indices of the time steps where InputsCrit$BoolCrit = FALSE or no data is available |
Laurent Coron, Ludovic Oudin, Olivier Delaigue
ErrorCrit_NSE
, ErrorCrit_KGE
, ErrorCrit_KGE2
library(airGR)
## loading catchment data
data(L0123001)
## preparation of the InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR,
Precip = BasinObs$P, PotEvap = BasinObs$E)
## run period selection
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d")=="1990-01-01"),
which(format(BasinObs$DatesR, format = "%Y-%m-%d")=="1999-12-31"))
## preparation of the RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J,
InputsModel = InputsModel, IndPeriod_Run = Ind_Run)
## simulation
Param <- c(X1 = 734.568, X2 = -0.840, X3 = 109.809, X4 = 1.971)
OutputsModel <- RunModel(InputsModel = InputsModel, RunOptions = RunOptions,
Param = Param, FUN = RunModel_GR4J)
## efficiency criterion: root-mean-square error
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_RMSE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_RMSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
## efficiency criterion: root-mean-square error on log-transformed flows
transfo <- "log"
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_RMSE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run],
transfo = transfo)
OutputsCrit <- ErrorCrit_RMSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
## efficiency criterion: Kling-Gupta Efficiency above a threshold (quant. 75 %)
BoolCrit <- BasinObs$Qmm[Ind_Run] >= quantile(BasinObs$Qmm[Ind_Run], 0.75, na.rm = TRUE)
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_RMSE, InputsModel = InputsModel,
RunOptions = RunOptions, Obs = BasinObs$Qmm[Ind_Run],
BoolCrit = BoolCrit)
OutputsCrit <- ErrorCrit_RMSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
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