Description Usage Arguments Value
View source: R/linear nonmyop.R View source: R/linear_nonmyop.R
Allocate treatments according to an information matrix based optimality criterion allowing for a non-myopic approach. Allow for dynamic covariates. We assume a linear model for the response and simulate responses sequentially.
1 2 | linear.nonmyop.dyn(covar, init, z.probs, k, N, int = NULL,
lossfunc = calc.D, stoc = F, ...)
|
covar |
a dataframe for the covariates |
init |
the number of units in the initial design |
z.probs |
vector of probabilities for each level of covariate z |
k |
integer for number of "outer" loops in coordinate exchange algorithm for initial design |
N |
natural number greater than 0 for horizon |
int |
set to T if you allow for treatment-covariate interactions in the model, NULL otherwise |
lossfunc |
the objective function to minimize |
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> |
Design matrix D
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