NoiseKriging::update
Description
Update a NoiseKriging model object with new points
Usage
Python
# k = NoiseKriging(...) k.update(y_u, noise_u, X_u)
R
# k = NoiseKriging(...) k$update(y_u, noise_u, X_u)
Matlab/Octave
% k = NoiseKriging(...) k.update(y_u, noise_u, X_u)
Arguments
Argument |
Description |
|---|---|
|
Numeric vector of new responses (output). |
|
Numeric vector of new noise variances (output). |
|
Numeric matrix of new input points. |
Examples
f <- function(x) 1- 1 / 2 * (sin(12 * x) / (1 + x) + 2 * cos(7 * x)*x^5 + 0.7)
plot(f)
set.seed(123)
X <- as.matrix(runif(10))
y <- f(X) + X/10 * rnorm(nrow(X))
points(X, y, col = "blue")
k <- NoiseKriging(y, (X/10)^2, X, "matern3_2")
x <- seq(from = 0, to = 1, length.out = 101)
p <- k$predict(x)
lines(x, p$mean, col = "blue")
polygon(c(x, rev(x)), c(p$mean - 2 * p$stdev, rev(p$mean + 2 * p$stdev)), border = NA, col = rgb(0, 0, 1, 0.2))
X_u <- as.matrix(runif(3))
y_u <- f(X_u) + 0.1 * rnorm(nrow(X_u))
points(X_u, y_u, col = "red")
## change the content of the object 'k'
k$update(y_u, rep(0.1^2,3), X_u)
x <- seq(from = 0, to = 1, length.out = 101)
p2 <- k$predict(x)
lines(x, p2$mean, col = "red")
polygon(c(x, rev(x)), c(p2$mean - 2 * p2$stdev, rev(p2$mean + 2 * p2$stdev)), border = NA, col = rgb(1, 0, 0, 0.2))
Results
