Maximum Entropy Synthetic Controls

abs_tstat | absolute value of the t statistic |

bin_search | Wrapper for bin_search_ which generates tolerances to search... |

bin_search_ | Perform binary search for the smallest balance which is... |

bin_search_balancer | Find the minimal amount of regularization possible |

clean_basque | Clean up the basque data that comes from the Synth package |

compute_att | Compute the ATT in the post-period |

compute_stat | Compute a test statistic statfunc(Y_t | t in times) |

concat_synth_out | Fit synthetic controls for multiple outcomes with random... |

create_index | Create an index of the outcomes with a weighted average |

cv_di | Cross validation for l2_entropy regularized synthetic... |

cv_kfold | Cross validation for l2_entropy regularized synthetic... |

cv_wz | Cross validation for l2_entropy regularized synthetic... |

double_screen | Screen covariates for the outcome process with LASSO and... |

ents | ents: A package for maximum entropy synthetic controls with... |

est_att | Fit weights and get att estimates |

firpo_inf | Get the permutation distribution of the test stat assuming... |

firpo_inf_synth | Get the permutation distribution of SC estimate test... |

fit_augsyn_formatted | Fit E[Y(0)|X] and for each post-period and balance pre-period |

fit_balancer_formatted | Find Balancing weights by solving the dual optimization... |

fit_dr | Fit a regularized outcome model and synthetic controls |

fit_dr_formatted | Fit a regularized outcome model and synthetic controls for a... |

fit_ebal_formatted | Fit entropy balancing weights |

fit_entropy | Fit l2 entropy regularized synthetic controls on outcomes... |

fit_entropy_formatted | Fit l2 entropy regularized synthetic controls by solving the... |

fit_gsynaug_formatted | Fit E[Y(0)|X] and for each post-period and balance pre-period |

fit_ipw | Fit IPW weights with a logit propensity score model |

fit_ipw_formatted | Fit IPW weights with a logit propensity score model |

fit_prog_gsynth | Use gsynth to fit factor model for E[Y(0)|X] |

fit_prog_reg | Use a separate regularized regression for each post period to... |

fit_prog_rf | Use a separate random forest regression for each post period... |

fit_progsyn_formatted | Fit E[Y(0)|X] and for each post-period and balance these |

fit_screensyn_formatted | Select covariates for E[Y(0)|X], then balance those |

fit_synth | Fit synthetic controls on outcomes, wrapper around... |

fit_synth_formatted | Fit synthetic controls on outcomes after formatting data |

fit_uniform_formatted | Use difference in means |

format_data | Format "long" panel data into "wide" matrices to fit... |

format_ipw | Format "long" panel data into "wide" matrices to fit IPW |

format_synth | Get the outcomes data into the correct form for Synth::synth |

format_synth_multi | Get multiple outcomes data as matrices |

get_augsyn | Fit outcome model and balance residuals |

get_balancer | Find Balancing weights by solving the dual optimization... |

get_dr | Fit a regularized outcome model and synthetic controls |

get_ebal | Fit entropy balancing weights |

get_entropy | Fit l2_entropy regularized synthetic controls on outcomes |

get_gsynaug | Fit gsynth and balance residuals |

get_index | Fit synthetic controls for multiple outcomes together with an... |

get_index_ent | Fit entropy regularized synthetic controls for multiple... |

get_index_syn | Fit synthetic controls for multiple outcomes together with an... |

get_ipw | Fit IPW weights with a logit propensity score model |

get_joint | Fit synthetic controls for multiple outcomes with the same... |

get_joint_ent | Fit entropy regularized synthetic controls for multiple... |

get_joint_syn | Fit synthetic controls for multiple outcomes with the same... |

get_progsyn | Fit synthetic controls on estimated outcomes under control |

get_screensyn | Fit synthetic controls on estimated outcomes under control |

get_separate | Fit synthetic controls for multiple outcomes separately |

get_separate_ent | Fit synthetic controls for multiple outcomes separately |

get_separate_syn | Fit synthetic controls for multiple outcomes separately |

get_synth | Fit synthetic controls on outcomes |

get_uniform | Use difference in means |

impute_controls | Impute the controls after fitting synth |

impute_dr | Impute the controls after fitting a dr estimator |

impute_gsynaug | Impute the controls after fitting gynsth and reweighting... |

impute_synaug | Impute the controls after fitting a dr estimator |

lasso_screen | Screen covariates for the outcome process |

lexical | Finds the lowest feasible tolerance in each group, holding... |

lexical_time | Finds the lowest feasible tolerance in each time period from... |

logsumexp | Compute numerically stable logsumexp |

logsumexp_grad | Compute numerically stable logsumexp gradient with natural... |

mean_abs | mean absolute difference |

plot_att | Plot the estimate of the att |

plot_outcomes | Plot the outcomes from a study/simulation |

prox_group | prox operator for group LASSO (generalization of prox_l2) |

prox_l1 | prox operator of sum(lam * abs(x)) |

prox_l2 | prox operator of lam * ||x||_2 |

recent_group | Lexically minimizes the imbalance in two groups, recent and... |

rmse_ratio | test stat is ratio of RMSEs in post and pre |

sep_lasso | Finds the lowest feasible tolerance in units of standard... |

sep_lasso_ | Internal function that does the work of sep_lasso |

sim_factor_model | Generate data from a factor model as in ADH 2010 (5) and... |

standard_error | Estimate the variance of the SC estimate |

standard_error_ | Internal function to estimate the variance of the SC estimate |

wpermtest | Get the permutation distribution of the test stat assuming... |

wpermtest2 | Get the permutation distribution of the test stat assuming... |

wpermtest2_sc | Get the weighted permutation distribution of SC estimate test... |

wpermtest_sc | Get the weighted permutation distribution of SC estimate test... |

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