# logLikelihoodFun.Kriging: Compute Log-Likelihood of Kriging Model In rlibkriging: Kriging Models using the 'libKriging' Library

 logLikelihoodFun.Kriging R Documentation

## Compute Log-Likelihood of Kriging Model

### Description

Compute Log-Likelihood of Kriging Model

### Usage

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

### Arguments

 `object` An S3 Kriging object. `theta` A numeric vector of (positive) range parameters at which the log-likelihood will be evaluated. `grad` Logical. Should the function return the gradient? `hess` Logical. Should the function return Hessian? `bench` Logical. Should the function display benchmarking output? `...` Not used.

### Value

The log-Likelihood computed for given `\boldsymbol{theta}`.

### Author(s)

Yann Richet yann.richet@irsn.fr

### 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, kernel = "matern3_2")
print(k)

ll <- function(theta) logLikelihoodFun(k, theta)\$logLikelihood

t <- seq(from = 0.001, to = 2, length.out = 101)
plot(t, ll(t), type = 'l')
abline(v = k\$theta(), col = "blue")
``````

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