Create a BOWL Object
.newBOWLStep(
moPropen,
fSet,
data,
response,
txName,
lambdas,
cvFolds,
kernel,
surrogate,
suppress,
guess,
prodPi,
index,
...
)
BOWLBasic object
model object for propensity
function specifying subsets or NULL
data.frame of covariates and tx
vector of responses
character indicating tx column in data
vector of tuning parameters
number of cross-validation folds or NULL
Kernel object
Surrogate object
vector of starting value for regime parameterse
vector of previous step propensity weights
vector indicating previous compliance with regime
additional inputs sent to optimization method