atkins: Assuming a linear model for the response, allocate treatment...

In mst1g15/biasedcoin:

Description

Assuming a linear model for the response, allocate treatment sequentially based on an optimal design criterion

Usage

atkins(covar, lossfunc = calc.D, int = NULL, init = 1,
  same.start = NULL, stoc = T, ...)

Arguments

covar	a dataframe for the covariates
lossfunc	the objective function to minimize
int	set to T if you allow for treatment-covariate interactions in the model, NULL otherwise
init	the number of units in the initial design, by default set to 1
same.start	the design matrix to be used for the initial design. If set to NULL, function generates initial design.
stoc	set to T if treatments are allocated using a stochastic method where the probability is determined by the optimality crtierion. Set to F if treatments are allocated deterministically
...	further arguments to be passed to <lossfunc>

Value

design matrix and value of objective function at each sample size

mst1g15/biasedcoin documentation built on Nov. 26, 2019, 4:01 a.m.