R: Simulating ED values under various scenarios

simDR {drc} | R Documentation

## Simulating ED values under various scenarios

### 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)

[Package drc version 3.0-1 Index]