future.logis: Calculate expected optimality for a given trajectory using...

In mst1g15/biasedcoin:

Description

Calculate expected optimality for a given trajectory using sequential approach. We assume a logistic model for the response.

Usage

future.logis(D.fix, n.r, z.probs, beta, int, sim, code = 0, lossfunc, ...)

Arguments

D.fix	Design matrix constructed using the true covariates in the experiment so far
n.r	length of trajectory to be simulated
z.probs	vector of probabilities for each level of covariate z
beta	current estimate of regression coefficients
int	set to T if you allow for treatment-covariate interactions in the model, NULL otherwise
sim	number of trajectories to simulate
code	set to NULL if (-1,1) coding is used for the treatments. Set to 0 if (0, 1) is used.
lossfunc	the objective function to minimize
...	further arguments to be passed to <lossfunc>

Value

loss of the design matrix which includes trajectory

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