future.loss.k: Assuming the currrent response, future covariate value and...

Description Usage Arguments Value

View source: R/linear nonmyop.R View source: R/linear_nonmyop.R

Description

Assuming the currrent response, future covariate value and future treatment, Calculate optimality if horizon is 1. If not, iterate back to exp.loss function.

Usage

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future.loss.k(z.next, t.next, z.now, t.now, zp, N, design, int, lossfunc,
  dyn = NULL, ...)

Arguments

z.next

vector of covariate values for future unit

t.next

treatment of future 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)

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 a real number if there are dynamic covariates

...

further arguments to be passed to <lossfunc>

Value

value of objective function one step ahead in the future, assuming z.next and t.next


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