lmtp_control function

Set LMTP Estimation Parameters

lmtp_control(
  .bound = 1e+05,
  .trim = 0.999,
  .learners_outcome_folds = 10,
  .learners_trt_folds = 10,
  .return_full_fits = FALSE
)

Arguments

• .bound: [numeric(1)]

  Determines that maximum and minimum values (scaled) predictions will be bounded by. The default is 1e-5, bounding predictions by 1e-5 and 0.9999.

• .trim: [numeric(1)]

  Determines the amount the density ratios should be trimmed. The default is 0.999, trimming the density ratios greater than the 0.999 percentile to the 0.999 percentile. A value of 1 indicates no trimming.

• .learners_outcome_folds: [integer(1)]

  The number of cross-validation folds for learners_outcome.

• .learners_trt_folds: [integer(1)]

  The number of cross-validation folds for learners_trt.

• .return_full_fits: [logical(1)]

  Return full SuperLearner fits? Default is FALSE, return only SuperLearner weights.

Returns

A list of parameters controlling the estimation procedure.

Examples

lmtp_control(.trim = 0.975)