Computes the constants required to make a function non-increasing on the specified interval. The output of this function is necessary to calculate the monotone optimal conditional error function.
The output object is a list that contains the intervals on which constant values are required, specified by the minimum dls and maximum dus of the interval and the respective constants, qs.
getMonotonisationConstants(
fun,
lower = 0,
upper = 1,
argument,
nSteps = 10^4,
epsilon = 10^(-5),
numberOfIterationsQ = 10^4,
design
)A list containing the monotonisation constants (element $qs) and the intervals on which they must be applied, specified via minimum (element qls) and maximum (element qus).
The function to be made monotone.
The lower limit of the interval on which the function should be monotonised. Must be a numeric value.
The upper limit of the interval on which the function should be monotonised.
The argument in which the function should be monotonised, given as a character.
The number of steps to be taken when checking the function for monotonicity. Must be a numeric value. Default 10^4.
Maximum allowed difference between the initial and monotone integral. Must be a numeric value. Default 10^-5.
Maximum number of iterations allowed to determine each value of q. Must be a numeric value. Default 10^4.
An object of class TrialDesignOptimalConditionalError created by getDesignOptimalConditionalErrorFunction(). Contains all necessary arguments to calculate the optimal conditional error function for the specified case.
Brannath, W., Dreher, M., zur Verth, J., Scharpenberg, M. (2024). Optimal monotone conditional error functions. https://arxiv.org/abs/2402.00814