compute_deriv_weights_gp: Calculate derivatives of CERF

View source: R/compute_deriv_weights_gp.R

compute_deriv_weights_gpR 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.


GPCERF documentation built on June 22, 2024, 11:30 a.m.