cr.future: Calculate (weighted) L-optimal expected optimality for a...

Description Usage Arguments Value

View source: R/lopt linear pseudononmy.R View source: R/lopt_linear_pseudononmy.R

Description

Calculate (weighted) L-optimal expected optimality for a given trajectory using sequential approach. We assume a linear model for the response.

Usage

1
cr.future(D.fix, n.r, sim, z.probs, lossfunc, cr, prior.scale, wr, ...)

Arguments

D.fix

Design matrix constructed using the true covariates in the experiment so far

n.r

length of trajectory to be simulated

sim

number of trajectories to simulate

z.probs

vector of probabilities for each level of covariate z

lossfunc

the objective function to minimize

cr

matrix of contrasts

prior.scale

prior scale parameter

wr

matrix of weights, set to NULL if equal weights

...

further arguments to be passed to <lossfunc>

Value

loss of the design matrix which includes trajectory


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