exp.loss.k: Break down the expected future objective function by cases...

In mst1g15/biasedcoin:

Description

Break down the expected future objective function by cases for every combination of: 1) future possible covariate 2) future possible treatment Find a weighted average across all these cases

Usage

## S3 method for class 'loss.k'
exp(z.now, t.now, zp, N, design, int, lossfunc, dyn = NULL,
  ...)

Arguments

z.now	vector of covariate values for current unit
t.now	treatment of current unit
zp	vector of probabilities for each level of covariate z (needs to in the same order as all.z)
N	natural number greater than 0 for horizon
design	design matrix constructed for all units up until the current unit
int	set to NULL if there are no interactions, set to T of there are interactions
lossfunc	the objective function to minimize
dyn	set to NULL of there are no dynamic covariates, set to T if there are dynamic covariates
...	further arguments to be passed to <lossfunc>

Value

design matrix D

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