.newQLearn {DynTxRegime} | R Documentation |
Perform a Step of the Q-Learning Algorithm
Description
Method performs all necessary regression and predictions steps for a single step of the Q-learning algorithm.
Usage
.newQLearn(response, ...)
## S4 method for signature 'vector'
.newQLearn(moMain, moCont, fSet, response, data, txName, iter, suppress)
## S4 method for signature 'QLearn'
.newQLearn(moMain, moCont, fSet, response, data, txName, iter, suppress)
Arguments
response |
a vector or the value object returned by a prior call to qlearn() |
moMain |
modeling object specifying the main effects component of the outcome model |
moCont |
modeling object specifying the contrasts component of the outcome model |
fSet |
function defining the feasible tx subsets |
data |
data.frame of covariates and tx received |
txName |
character name of tx variable in data |
iter |
the maximum number of iterations in the iterative algorithm |
suppress |
logical indicating user's screen printing preference |
Value
an object of class QLearn.
[Package DynTxRegime version 4.15 Index]