get_entropy: Fit l2_entropy regularized synthetic controls on outcomes

In ebenmichael/ents: Maximum Entropy Synthetic Controls

Description

Fit l2_entropy regularized synthetic controls on outcomes

Usage

get_entropy(outcomes, metadata, trt_unit = 1, eps = NULL,
  outcome_col = NULL, lasso = FALSE, cols = list(unit = "unit", time =
  "time", outcome = "outcome", treated = "treated"), max_iters = 1000,
  tol = 1e-08)

Arguments

outcomes	Tidy dataframe with the outcomes and meta data
metadata	Dataframe of metadata
trt_unit	Unit that is treated (target for regression), default: 0
eps	Bound on synthetic control differences
outcome_col	Column name which identifies outcomes, if NULL then assume only one outcome
lasso	Whether to do lasso (every covariate is separate)
cols	Column names corresponding to the units, time variable, outcome, and treated indicator
max_iters	Maximum number of iterations
tol	Convergence tolerance

Value

outcomes with additional synthetic control added and weights

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