future.y: Assuming a current response, break down the expected future...

In mst1g15/biasedcoin:

Description

Assuming a current response, break down the expected future optimality by cases for every combination of: 1) future possible covariate 2) future possible treatment Find a weighted average across all these cases

Usage

future.y(y.now, z.now, t.now, zp, N, design, int, lossfunc, beta, y, bayes,
  dyn = NULL, ...)

Arguments

y.now	scalar for the response of current unit
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 below)
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
beta	estimate of the regression coefficients
y	responses that have been observed up until the current unit
bayes	set to T if bayesglm is used instead of glm. Default prior assumed.
dyn	set to T if there is a dynamic covariate
...	further arguments to be passed to <lossfunc>

Value

expected value of objective function assuming a current response

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