logMargPostFun.Kriging: Compute the log-marginal posterior of a kriging model, using...

In rlibkriging: Kriging Models using the 'libKriging' Library

Compute the log-marginal posterior of a kriging model, using the prior XXXY.

Description

Compute the log-marginal posterior of a kriging model, using the prior XXXY.

Usage

## S3 method for class 'Kriging'
logMargPostFun(object, theta, grad = FALSE, bench = FALSE, ...)

Arguments

object	S3 Kriging object.
theta	Numeric vector of correlation range parameters at which the function is to be evaluated.
grad	Logical. Should the function return the gradient (w.r.t theta)?
bench	Logical. Should the function display benchmarking output?
...	Not used.

Value

The value of the log-marginal posterior computed for the given vector theta.

Author(s)

Yann Richet [e-mail]

References

XXXY A reference describing the model (prior, ...)

See Also

rgasp in the RobustGaSP package.

Examples

f <- function(x) 1 - 1 / 2 * (sin(12 * x) / (1 + x) + 2 * cos(7 * x) * x^5 + 0.7)
set.seed(123)
X <- as.matrix(runif(10))
y <- f(X)

k <- Kriging(y, X, "matern3_2", objective="LMP")
print(k)

lmp <- function(theta) logMargPostFun(k, theta)$logMargPost

t <- seq(from = 0.01, to = 2, length.out = 101)
plot(t, lmp(t), type = "l")
abline(v = k$theta(), col = "blue")

rlibkriging documentation built on July 9, 2023, 5:53 p.m.