crumble_control: Crumble control parameters

In crumble: Flexible and General Mediation Analysis Using Riesz Representers

Crumble control parameters

Description

Crumble control parameters

Usage

crumble_control(
  crossfit_folds = 10L,
  mlr3superlearner_folds = 10L,
  zprime_folds = 1L,
  epochs = 100L,
  learning_rate = 0.01,
  batch_size = 64,
  device = c("cpu", "cuda", "mps")
)

Arguments

crossfit_folds	[numeric(1)] The number of crossfit folds.
mlr3superlearner_folds	[numeric(1)] The number of 'mlr3superlearner' folds.
zprime_folds	[numeric(1)] The number of folds to split that data into for calculating Z'. With larger sample sizes, a larger number will increase speed.
epochs	[numeric(1)] The number of epochs to train the neural network.
learning_rate	[numeric(1)] The learning rate for the neural network.
batch_size	[numeric(1)] The batch size for mini-batch gradient descent.
device	[character(1)] Object representing the device on which a torch_tensor is or will be allocated.

Value

A list of control parameters

Examples

if (torch::torch_is_installed()) crumble_control(crossfit_folds = 5)

crumble documentation built on April 13, 2025, 5:10 p.m.