compute_deriv_nn {GPCERF} | R Documentation |
Calculates the posterior mean of the derivative of CERF at a given exposure level with nnGP.
compute_deriv_nn(
w,
w_obs,
gps_m,
y_obs,
hyperparam,
n_neighbor,
block_size,
kernel_fn = function(x) exp(-x),
kernel_deriv_fn = function(x) -exp(-x)
)
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 |
y_obs |
A vector of observed outcome values. |
hyperparam |
A vector of hyper-parameters in the GP model. |
n_neighbor |
The number of nearest neighbors on one side. |
block_size |
The number of samples included in a computation block.
Mainly used to balance the speed and memory requirement. Larger
|
kernel_fn |
The covariance function. The input is the square of Euclidean distance. |
kernel_deriv_fn |
The partial derivative of the covariance function. The input is the square of Euclidean distance. |
A scalar of estimated derivative of CERF at w
in nnGP.