Simulating ED values under various scenarios

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Description

Simulating ED values for a given model and given dose values.

Usage

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  simDR(mpar, sigma, fct, noSim = 1000, conc, edVec = c(10, 50), seedVal = 20070723)

Arguments

mpar

numeric vector of model parameters

sigma

numeric specifying the residual standard deviation

fct

list supplying the chosen mean function

conc

numeric vector of concentration/dose values

edVec

numeric vector of ED values to estimate in each simulation

noSim

numeric giving the number of simulations

seedVal

numeric giving the seed used to initiate the random number generator

Details

The arguments mpar and sigma are typically obtained from a previous model fit.

Only dose-response models assuming normally distributed errors can be used.

Value

A list of matrices with as many components as there are chosen ED values. The entries in the matrices are empirical standard deviations of the estimated ED values. Row-wise from top to bottom more and more concentration/dose values are included in the simulations; top row starting with 5 concentrations. The number of replicates increases column by column from left to right.

The list is returned invisbly as the matrices also are displayed.

Author(s)

Christian Ritz

Examples

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ryegrass.m1 <- drm(ryegrass, fct=LL.4())

simDR(coef(ryegrass.m1), sqrt(summary(ryegrass.m1)$resVar), LL.4(), 2, 
c(1.88, 3.75, 7.50, 0.94, 15, 0.47, 30, 0.23, 60), seedVal = 200710291)

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