HDCATE.inference: Construct uniform confidence bands

In hdcate: Estimation of Conditional Average Treatment Effects with High-Dimensional Data

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 FALSE

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)

hdcate documentation built on Dec. 16, 2022, 5:19 p.m.