compute_m_sigma {GPCERF}R Documentation

Compute mean, credible interval, and covariate balance in standard Gaussian process (GP)

Description

Calculates the induced covariate balance associated with one hyper-parameter configuration in standard GP.

Usage

compute_m_sigma(
  hyperparam,
  outcome_data,
  treatment_data,
  covariates_data,
  w,
  gps_m,
  tuning,
  kernel_fn = function(x) exp(-x^2)
)

Arguments

hyperparam

A vector of values of hyper-parameters.

  • First element: alpha

  • Second element: beta

  • Third element: g_sigma (gamma / sigma)

outcome_data

A vector of outcome data.

treatment_data

A vector of treatment data.

covariates_data

A data frame of covariates data.

w

A vector of exposure levels at which the CERF is estimated.

gps_m

An S3 gps object including: gps: A data.frame of GPS vectors. - Column 1: GPS - Column 2: Prediction of exposure for covariate of each data sample (e_gps_pred). - Column 3: Standard deviation of e_gps (e_gps_std) used_params: - dnorm_log: TRUE or FLASE

tuning

The function is used for parameter tuning (default = TRUE) or estimation (FALSE)

kernel_fn

The covariance function of GP.

Value

A list containing two elements:


[Package GPCERF version 0.2.4 Index]