estimate_gps | R Documentation |
Estimates GPS value for each observation using parametric or non-parametric approaches.
estimate_gps( Y, w, c, gps_model = "parametric", internal_use = TRUE, params = list(), sl_lib = c("m_xgboost"), nthread = 1, ... )
Y |
A vector of observed outcome variable. |
w |
A vector of observed continuous exposure variable. |
c |
A data frame of observed covariates variable. |
gps_model |
Model type which is used for estimating GPS value, including parametric (default) and non-parametric. |
internal_use |
If TRUE will return helper vectors as well. Otherwise, will return original data + GPS values. |
params |
Includes list of parameters that are used internally. Unrelated parameters will be ignored. |
sl_lib |
A vector of prediction algorithms. |
nthread |
An integer value that represents the number threads to be used in a shared memory system. |
... |
Additional arguments passed to the model. |
The function returns a S3 object. Including the following:
Original data set + GPS, counter, row_index values (Y, w, GPS, counter_weight, row_index, c)
e_gps_pred
e_gps_std_pred
w_resid
gps_mx (min and max of gps)
w_mx (min and max of w).
used_params
If internal.use
is set to be FALSE, only original data set + GPS will
be returned.
The outcome variable is not used in estimating the GPS value. However, it is used in compiling the data set with GPS values.
m_d <- generate_syn_data(sample_size = 100) data_with_gps <- estimate_gps(m_d$Y, m_d$treat, m_d[c("cf1","cf2","cf3","cf4","cf5","cf6")], gps_model = "parametric", internal_use = FALSE, params = list(xgb_max_depth = c(3,4,5), xgb_nrounds=c(10,20,30,40,50,60)), nthread = 1, sl_lib = c("m_xgboost") )
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