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 |
bootstrap_bal | Bootstrap standard errors for estimated counterfactual with... |
bootstrap_ridgeaug | Bootstrap standard errors for estimated counterfactual with... |
bootstrap_sc | Bootstrap standard errors for estimated counterfactual with... |
cherno_test | Weighted Least Squares Standard Errors |
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_bal | Cross validation for balancing weights, DI style Uses the CV... |
cv_kfold_bal | Cross validation for balancing weights K-fold cross... |
cv_wz_bal | Cross validation for l2_entropy regularized synthetic... |
di_standard_error | Estimate the variance of the SC estimate |
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_ipw | Fit IPW weights with a logit propensity score model |
fit_ipw_formatted | Fit IPW weights with a logit propensity score model |
fit_prog_causalimpact | Fit a bayesian structural time series to fit E[Y(0)|X] |
fit_prog_cits | Fit a Comparitive interupted time series to fit E[Y(0)|X] |
fit_prog_complete | Use nuclear norm matrix completion to fit outcome model |
fit_prog_gsynth | Use gsynth to fit factor model for E[Y(0)|X] |
fit_prog_mcpanel | Use Athey (2017) matrix completion panel data code |
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_prog_seq2seq | Fit a seq2seq model with a feedforward net to fit E[Y(0)|X] |
fit_progsyn_formatted | Fit E[Y(0)|X] and for each post-period and balance these |
fit_residaug_formatted | Fit E[Y(0)|X] and for each post-period and balance pre-period |
fit_ridgeaug_cov_formatted | Ridge augmented weights with covariates |
fit_ridgeaug_formatted | Ridge augmented weights |
fit_screensyn_formatted | Select covariates for E[Y(0)|X], then balance those |
fit_svd_formatted | Fit synthetic controls on outcomes after performing SVD |
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_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_residaug | Fit outcome model and balance residuals |
get_ridgeaug | Fit synthetic controls on outcomes |
get_ridgeaug_cov | Fit synthetic controls on outcomes |
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_svd_bal | Find Balancing weights by solving the dual optimization... |
get_svd_syn | Find Balancing weights by solving the dual optimization... |
get_synth | Fit synthetic controls on outcomes |
get_uniform | Use difference in means |
get_wlsaug | Get weights then fit outcome model with weighted loss... |
importance_test | Estimate p-value with non-uniform probabilities of treatment... |
importance_test_sc | Get the weighted permutation distribution of SC estimate test... |
impute_controls | Impute the controls after fitting synth |
impute_dr | Impute the controls after fitting a dr estimator |
impute_residaug | 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... |
loo_se_ridgeaug | Use leave out one estimates (placebo gaps) to estimate... |
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_ | Internal function to estimate the variance of the SC estimate |
svyglm_se_ | Compute standard errors from survey glm |
svyglm_se_synth | svyglm standard errors |
valid_test | Estimate p-value with non-uniform probabilities of treatment... |
weighted_test | Estimate p-value with non-uniform probabilities of treatment... |
weighted_test_bal | Get the weighted permutation distribution of SC estimate test... |
weighted_test_sc | Get the weighted permutation distribution of SC estimate test... |
wls_se_ | Compute model-based weighted least squares SE estimates of... |
wls_se_bal | Bootstrap standard errors for estimated counterfactual with... |
wls_se_ridgeaug | Weighted Least Squares Standard Errors |
wls_se_synth | Weighted Least Squares Standard Errors |
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... |
wvar_se_ridgeaug | Use closed form weighted variance estiamte for... |
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