Calculates default bounds for non-linear parameters in dose-response models

Calculates reasonable bounds for non-linear parameters for the built-in non-linear regression model based on the dose range under investigation.

Usage

defBnds(
  mD,
  emax = c(0.001, 1.5) * mD,
  exponential = c(0.1, 2) * mD,
  logistic = matrix(c(0.001, 0.01, 1.5, 1/2) * mD, 2),
  sigEmax = matrix(c(0.001 * mD, 0.5, 1.5 * mD, 10), 2),
  betaMod = matrix(c(0.05, 0.05, 4, 4), 2)
)

Arguments

mD

Maximum dose in the study.

emax, exponential, logistic, sigEmax, betaMod

values for the nonlinear parameters for these model-functions

Value

List containing bounds for the model parameters.

Details

For the logistic model the first row corresponds to the ED50 parameter and the second row to the delta parameter. For the sigmoid Emax model the first row corresponds to the ED50 parameter and the second row to the h parameter, while for the beta model first and second row correspond to the delta1 and delta2 parameters. See logistic(), sigEmax() and betaMod() for details.

See also

fitMod()

Author

Bjoern Bornkamp

Examples

  defBnds(mD = 1)
#> $emax
#> [1] 0.001 1.500
#> 
#> $logistic
#>       [,1] [,2]
#> [1,] 0.001  1.5
#> [2,] 0.010  0.5
#> 
#> $sigEmax
#>       [,1] [,2]
#> [1,] 0.001  1.5
#> [2,] 0.500 10.0
#> 
#> $exponential
#> [1] 0.1 2.0
#> 
#> $betaMod
#>      [,1] [,2]
#> [1,] 0.05    4
#> [2,] 0.05    4
#> 
  defBnds(mD = 200)
#> $emax
#> [1]   0.2 300.0
#> 
#> $logistic
#>      [,1] [,2]
#> [1,]  0.2  300
#> [2,]  2.0  100
#> 
#> $sigEmax
#>      [,1] [,2]
#> [1,]  0.2  300
#> [2,]  0.5   10
#> 
#> $exponential
#> [1]  20 400
#> 
#> $betaMod
#>      [,1] [,2]
#> [1,] 0.05    4
#> [2,] 0.05    4
#>