cv_wz_bal: Cross validation for l2_entropy regularized synthetic...

Description Usage Arguments Value

Description

Cross validation for l2_entropy regularized synthetic controls Take bootstrap samples over the controls and evaluate balance Modified version of Wang & Zubizaretta (2018)

Usage

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cv_wz_bal(outcomes, metadata, n_boot, hyperparams, link = c("logit", "linear",
  "pos-linear"), regularizer = c(NULL, "l1", "l2", "ridge", "linf"),
  normalized = TRUE, outcome_col = NULL, cols = list(unit = "unit", time =
  "time", outcome = "outcome", treated = "treated"), opts = list())

Arguments

outcomes

Tidy dataframe with the outcomes and meta data

metadata

Dataframe of metadata

hyperparams

Vector of hyper-parameter settings to consider

regularizer

Dual of balance criterion

normalized

Whether to normalize the weights

outcome_col

Column name which identifies outcomes, if NULL then assume only one outcome

cols

Column names corresponding to the units, time variable, outcome, and treated indicator

opts

Optimization options

  • MAX_ITERS Maximum number of iterations to run

  • EPS Error tolerance

Value

best hyperparameter


ebenmichael/ents documentation built on May 31, 2019, 8:45 p.m.