newBOWLStep function

Create a BOWL Object

.newBOWLStep(
  moPropen,
  fSet,
  data,
  response,
  txName,
  lambdas,
  cvFolds,
  kernel,
  surrogate,
  suppress,
  guess,
  prodPi,
  index,
  ...
)

Arguments

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

Returns

BOWLBasic object