mixtox (version 1.2)

nmECx: Effect Concentration Calculation for Non-monotonic Curves

Description

Effect concentrations are calculated at particular effects based on the fitting coefficients of 13 monotonic equations.

Usage

nmECx(model, param, effv, minx)

Arguments

model

character vector of equations:("Brain_Consens", "BCV", "Beckon", "Biphasic", "Hill_six")

param

numeric matrix of fitting coefficients with rownames (equation selected) and colnames (ALpha, Beta, Gamma, Delta, and Epsilon).

effv

numeric vector with single or multiple effect values (miny ~ 1)

minx

numeric vector with single or multiple concentrations that induce maximun stimulation

Value

• a numeric vector of effect concentration(s)

Details

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 using curveFit

References

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. Di Veroli GY, Fornari C, Goldlust I, Mills G, Koh SB, Bramhall JL, et al. 2015. An automated fitting procedure and software for dose-response curves with multiphasic features. Scitific Report 5: 14701. Reference to {curveFit}

See Also

CEx curveFit

Examples

## example 1
# calculate ECL-10, ECR-10, EC5, and EC50 of the four hormesis 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)