compute_deriv_weights_gp {GPCERF}R Documentation

Calculate derivatives of CERF

Description

Calculates the weights assigned to each observed outcome when deriving the posterior mean of the first derivative of CERF at a given exposure level.

Usage

compute_deriv_weights_gp(
  w,
  w_obs,
  gps_m,
  hyperparam,
  kernel_fn = function(x) exp(-x),
  kernel_deriv_fn = function(x) -exp(-x)
)

Arguments

w

A scalar of exposure level of interest.

w_obs

A vector of observed exposure levels of all samples.

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 FALSE

hyperparam

A vector of hyper-parameters in the GP model.

kernel_fn

The covariance function.

kernel_deriv_fn

The partial derivative of the covariance function.

Value

A vector of weights for all samples, based on which the posterior mean of the derivative of CERF at the exposure level of interest is calculated.


[Package GPCERF version 0.2.4 Index]