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

In mst1g15/biasedcoin:

Description

Assuming the currrent response, future covariate value and future treatment, Calculate objective function if horizon is 1. If horizon >1, iterate back to cr.exp.loss function.

Usage

cr.future.loss(z.next, t.next, zp, N, design, k, beta, y, cr, wr, prior.scale,
  bayes, dyn = NULL, Nprobs = NULL, ...)

Arguments

z.next	vector of covariate values for future unit
t.next	treatment of future 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
k	number of covariates
beta	vector of current estimates for regression coefficients
y	vectir of responses generated up until current unit
cr	matrix of contrasts
wr	matrix of weights
prior.scale	prior scale parameter
bayes	set to T if bayesglm is used instead of glm. Default prior assumed
dyn	set to NULL of there are no dynamic covariates, set to T if there are dynamic covariates
Nprobs	a counter to be used if there are dynamic covariates
...	further arguments to be passed to <lossfunc>

Value

value of objective function assuming current response, future covariate value and future treatment

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