lmtp_control: Set LMTP Estimation Parameters

In lmtp: Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies

Set LMTP Estimation Parameters

Description

Set LMTP Estimation Parameters

Usage

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.

Value

A list of parameters controlling the estimation procedure.

Examples

lmtp_control(.trim = 0.975)

lmtp documentation built on June 27, 2024, 9:10 a.m.