`NoiseKriging::copy`

Description

Duplicate a NoiseKriging Model

Usage

Python
```
# k = NoiseKriging(...)
k2 = k.copy()
```

R

# k = NoiseKriging(...)
k2 = k$copy() # or copy(k)

Matlab/Octave
```
% k = NoiseKriging(...)
k2 = k.copy()
```

Value

The copy of object.

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) + X/10 * rnorm(nrow(X)) # add noise dep. on X

k <- NoiseKriging(y, noise=(X/10)^2, X, kernel = "matern3_2")
k
k$copy()

Results

* data: 10x[0.0455565,0.940467] -> 10x[0.152144,0.957381]
  * noise: 10x[2.07539e-05,0.00884479]
* trend constant (est.): 0.487335
* variance (est.): 0.0635381
* covariance:
  * kernel: matern3_2
  * range (est.): 0.211413
  * fit:
    * objective: LL
    * optim: BFGS
* data: 10x[0.0455565,0.940467] -> 10x[0.152144,0.957381]
  * noise: 10x[2.07539e-05,0.00884479]
* trend constant (est.): 0.487335
* variance (est.): 0.0635381
* covariance:
  * kernel: matern3_2
  * range (est.): 0.211413
  * fit:
    * objective: LL
    * optim: BFGS