GOF | R Documentation |

Standard GOF metrics Startvalues for sampling with nrChains > 1 : if you want to provide different start values for the different chains, provide a list

GOF(observed, predicted, plot = F, centered = T)

`observed` |
observed values |

`predicted` |
predicted values |

`plot` |
should a plot be created |

`centered` |
if T, variables are centered to the mean of the observations, i.e. the intercept is for the mean value of the observation |

The function considers observed ~ predicted and calculates

rmse = root mean squared error

mae = mean absolute errorr

a linear regression with slope, intercept and coefficient of determination R2

For the linear regression, centered = T means that variables will be centered around the mean value of the observation. This setting avoids a correlation between slope and intercept (that the intercept is != 0 as soon as the slope is !=0)

A list with the following entries: rmse = root mean squared error, mae = mean absolute error, slope = slope of regression, offset = intercept of regression, R2 = R2 of regression

In principle, it is possible to plot observed ~ predicted and predicted ~ observed. However, if we assume that the error is mainly on the y axis (observations), i.e. that observations scatter around the true (ideal) value, we should plot observed ~ predicted. See Pineiro et al. (2008). How to evaluate models: observed vs. predicted or predicted vs. observed?. Ecological Modelling, 216(3-4), 316-322.

Florian Hartig

x = runif(500,-1,1) y = 0.2 + 0.9 *x + rnorm(500, sd = 0.5) summary(lm(y ~ x)) GOF(x,y) GOF(x,y, plot = TRUE)

BayesianTools documentation built on Feb. 16, 2023, 8:44 p.m.

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