criteriaCheck {BeeGUTS} | R Documentation |
Computes PPC and NRMSE as defined in EFSA 2018
criteriaCheck(x)
x |
an object of class |
The function returns a list with three items:
PPC |
The criterion, in percent, compares the predicted median number of survivors associated
to their uncertainty limits with the observed numbers of survivors.
Based on experience, PPC resulting in more than |
NRMSE |
The criterion, in percent, is based on the classical root-mean-square error (RMSE), used to aggregate the magnitudes of the errors in predictions for various time-points into a single measure of predictive power. In order to provide a criterion expressed as a percentage, NRMSE is the normalised RMSE by the mean of the observations. EFSA (2018) recognised that a NRMSE of less than 50% indicates good model performance |
SPPE |
A list with the Survival Probability Prediction Error per dataset and condition. Each dataset is in a sublist. |
@references EFSA PPR Scientific Opinion (2018) Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms https://www.efsa.europa.eu/en/efsajournal/pub/5377
@example data(fitBetacyfluthrin_Chronic) out <- criteriaCheck(fitBetacyfluthrin_Chronic)