gradKm_dnewdata: Gradient of posterior mean and variance

In profExtrema: Compute and Visualize Profile Extrema Functions

Description

Computes the gradient of the posterior mean and variance of the kriging model in object at the points newdata.

Usage

gradKm_dnewdata(object, newdata, type, se.compute = TRUE,
  light.return = FALSE, bias.correct = FALSE)

Arguments

object	a km object
newdata	a vector, matrix or data frame containing the points where to perform predictions.
type	a character corresponding to the type of kriging family ("SK" or "UK").
se.compute	an optional boolean indicating whether to compute the posterior variance or not. Default is TRUE.
light.return	an optional boolean indicating whether to return additional variables. Default is FALSE.
bias.correct	an optional boolean to correct bias in the UK variance. Default is FALSE.

Value

Returns a list containing

• mean: the gradient of the posterior mean at newdata.

• trend: the gradient of the trend at newdata.

• s2: the gradient of the posterior variance at newdata.

Author(s)

Dario Azzimonti

profExtrema documentation built on March 22, 2020, 1:07 a.m.