grab_loss
Extract the RMSE loss of the optimized weights from the synth pipeline.
grab_loss(data)
data |
nested data of type |
tibble data frame
# Smoking example data data(smoking) smoking_out <- smoking %>% # initial the synthetic control object synthetic_control(outcome = cigsale, unit = state, time = year, i_unit = "California", i_time = 1988, generate_placebos=TRUE) %>% # Generate the aggregate predictors used to generate the weights generate_predictor(time_window=1980:1988, lnincome = mean(lnincome, na.rm = TRUE), retprice = mean(retprice, na.rm = TRUE), age15to24 = mean(age15to24, na.rm = TRUE)) %>% generate_predictor(time_window=1984:1988, beer = mean(beer, na.rm = TRUE)) %>% generate_predictor(time_window=1975, cigsale_1975 = cigsale) %>% generate_predictor(time_window=1980, cigsale_1980 = cigsale) %>% generate_predictor(time_window=1988, cigsale_1988 = cigsale) %>% # Generate the fitted weights for the synthetic control generate_weights(optimization_window =1970:1988, Margin.ipop=.02,Sigf.ipop=7,Bound.ipop=6) %>% # Generate the synthetic control generate_control() # grab the MSPE loss from the optimization of the weights. smoking_out %>% grab_loss()
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