HDCATE.inference {hdcate} | R Documentation |
Construct uniform confidence bands
Description
Construct uniform confidence bands
Usage
HDCATE.inference(
HDCATE_model,
sig_level = 0.01,
n_rep_boot = 1000,
verbose = FALSE
)
Arguments
HDCATE_model |
an object created via HDCATE |
sig_level |
a (vector of) significant level, such as 0.01, or c(0.01, 0.05, 0.10) |
n_rep_boot |
repeat n times for bootstrap, the default is 1000 |
verbose |
whether the verbose message is displayed, the default is |
Value
None. The HDCATE confidence bands are constructed.
Examples
# get simulation data
n_obs <- 500 # Num of observations
n_var <- 100 # Num of observed variables
n_rel_var <- 4 # Num of relevant variables
data <- HDCATE.get_sim_data(n_obs, n_var, n_rel_var)
# conditional expectation model is misspecified
x_formula <- paste(paste0('X', c(2:n_var)), collapse ='+')
# propensity score model is misspecified
# x_formula <- paste(paste0('X', c(1:(n_var-1))), collapse ='+')
# create a new HDCATE model
model <- HDCATE(data=data, y_name='Y', d_name='D', x_formula=x_formula)
HDCATE.set_condition_var(model, 'X2', min=-1, max=1, step=0.01)
HDCATE.fit(model)
HDCATE.inference(model)
[Package hdcate version 0.1.0 Index]