nmECx | R Documentation |

Effect concentrations are calculated at particular effects based on the fitting coefficients of J-shaped Models.

nmECx(model, param, effv, minx, gap = -1e-6, sav = FALSE)

`model` |
a character vector of equations:("Brain_Consens", "BCV", "Biphasic", "Hill_five"). |

`param` |
a numeric matrix of fitting coefficients with rownames (models) and colnames (ALpha, Beta, Gamma, Delta, and Epsilon). |

`effv` |
a numeric value (vector) with single or multiple effect values (miny ~ 1). |

`minx` |
a numeric value (vector) with single or multiple concentrations that induce maximun stimulation. |

`gap` |
theoritical response at the extreme low concentration predicted by a fitted model. |

`sav` |
TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory. |

effect concentrations will be calculated with provided equations(model),
associated fitting
parameters (param), and effects (effv). Effect (effv) should be a value(s) between miny ~ 1. For
example, *effv* should be 0.5 if we want to calculate a concentration causes 50% effect.
*minx* should be calculated by curveFit or tuneFit.

`ecx ` |
a numeric vector of effect concentration. |

Zhu X-W, Liu S-S, Qin L-T, Chen F, Liu H-L. 2013. Modeling non-monotonic dose-response
relationships: Model evaluation and hormetic quantities exploration. Ecotoxicology and
Environmental Safety 89:130-136.

`CEx`

`curveFit`

## example 1 # calculate ECL-10, ECR-10, EC5, and EC50 of the four hormetic curves model <- hormesis$sgl$model param <- hormesis$sgl$param minx <- hormesis$sgl$minx nmECx(model, param, effv = c(-0.10, 0.05, 0.50), minx)

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