leaveOneOutFun.Kriging {rlibkriging} | R Documentation |
Compute Leave-One-Out (LOO) error for an object with S3 class
"Kriging"
representing a kriging model.
Description
The returned value is the sum of squares \sum_{i=1}^n [y_i -
\hat{y}_{i,(-i)}]^2
where \hat{y}_{i,(-i)}
is the
prediction of y_i
based on the the observations y_j
with j \neq i
.
Usage
## S3 method for class 'Kriging'
leaveOneOutFun(object, theta, grad = FALSE, bench = FALSE, ...)
Arguments
object |
A |
theta |
A numeric vector of range parameters at which the LOO will be evaluated. |
grad |
Logical. Should the gradient (w.r.t. |
bench |
Logical. Should the function display benchmarking output |
... |
Not used. |
Value
The leave-One-Out value computed for the given vector
\boldsymbol{\theta}
of correlation ranges.
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", objective = "LOO", optim="BFGS")
print(k)
loo <- function(theta) leaveOneOutFun(k, theta)$leaveOneOut
t <- seq(from = 0.001, to = 2, length.out = 101)
plot(t, loo(t), type = "l")
abline(v = k$theta(), col = "blue")
[Package rlibkriging version 0.8-0.1 Index]