simDR: Simulating ED values under various scenarios

In MaximeBSanofi/drc2:

Description

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

Usage

  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

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)

MaximeBSanofi/drc2 documentation built on Feb. 22, 2022, 12:02 a.m.