estimate_npmetric_erf {CausalGPS} | R Documentation |
Estimate smoothed exposure-response function (ERF) for matched and weighted data set using non-parametric models.
estimate_npmetric_erf(
matched_Y,
matched_w,
matched_counter = NULL,
bw_seq = seq(0.2, 2, 0.2),
w_vals,
nthread
)
matched_Y |
a vector of outcome variable in the matched set. |
matched_w |
a vector of continuous exposure variable in the matched set. |
matched_counter |
a vector of counter variable in the matched set. |
bw_seq |
a vector of bandwidth values (Default is seq(0.2,2,0.2)). |
w_vals |
a vector of values that you want to calculate the values of the ERF at. |
nthread |
number of available cores. |
Estimate Functions Using Local Polynomial kernel regression Package: ‘KernSmooth’.
The function returns a gpsm_erf object. The object includes the following attributes:
params
matched_Y
matched_w
bw_seq
w_vals
erf
fcall
m_d <- generate_syn_data(sample_size = 100)
pseudo_pop <- generate_pseudo_pop(m_d$Y,
m_d$treat,
m_d[c("cf1","cf2","cf3","cf4","cf5","cf6")],
ci_appr = "matching",
pred_model = "sl",
sl_lib = c("m_xgboost"),
params = list(xgb_nrounds=c(10,20,30),
xgb_eta=c(0.1,0.2,0.3)),
nthread = 1,
covar_bl_method = "absolute",
covar_bl_trs = 0.1,
covar_bl_trs_type="mean",
max_attempt = 1,
matching_fun = "matching_l1",
delta_n = 1,
scale = 0.5)
erf_obj <- estimate_npmetric_erf(pseudo_pop$pseudo_pop$Y,
pseudo_pop$pseudo_pop$w,
bw_seq=seq(0.2,2,0.2),
w_vals = seq(2,20,0.5),
nthread = 1)