R2nls | R Documentation |

This function calculates measures of goodness of fit for nonlinear regression. It works with both 'nls' and 'drc' objects

R2nls(object)

`object ` |
A nonlinear regression fit object. It can be either a 'nls' fit or 'drm' fit. |

A list with the following slots:

`R2 ` |
Traditional coefficient of determination, calculated as the ratio of model SS to total SS. Formula as in Schabenberger and Pierce, 5.23, pag 211. |

`PseudoR2 ` |
Pseudo-R2, more useful for nonlinear regression with no-intercept-models. Formula Formula as in Schabenberger and Pierce, 5.24, pag 212. |

`R2adj ` |
Adjusted R2, similar to R2 above, but penalised for higher number of parameters. |

`MSE ` |
Mean Squared Error |

`RMSE ` |
Root Means Squared Error |

`RRMSE ` |
Relative Root Means Squared Error |

Andrea Onofri

Schabenberger, O., Pierce, F.J., 2002. Contemporary statistical models for the plant and soil sciences. Taylor & Francis, CRC Press, Books.

data(beetGrowth) mod3 <- nls(weightInf ~ NLS.L3(DAE, b, c, d), data = beetGrowth) R2nls(mod3) mod4 <- drm(weightInf ~ DAE, fct = L.3(), data = beetGrowth) R2nls(mod4)

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