criteriaCheck {BeeGUTS} | R Documentation |

## Computes PPC and NRMSE as defined in EFSA 2018

### Description

Computes PPC and NRMSE as defined in EFSA 2018

### Usage

```
criteriaCheck(x)
```

### Arguments

`x` |
an object of class |

### Value

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)

*BeeGUTS*version 1.1.3 Index]