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krisp toolbox >> krisp toolbox > SimCondGaussian

SimCondGaussian

Creates conditional gaussian process simulations.

Calling Sequence

Sim=SimCondGaussian (Xnew,model,ns);

Parameters

Xnew:

data points for simulations (mx*n). Row vectors representing data points.

model:

kriging model, mlist of type kmodel created previously.

ns:

number of simulations. Default value ns=1.

Sim:

matrix containing simulated function values at data points Xnew (m*ns).

Description

Creates Conditional Gaussian process simulations at Xnew data points, given observations and covariance model by kriging model. Note- This function uses gobal variable S_kriging, T_kriging.

Examples

// 1D example
x_bound=[-2; 2];
X=(linspace(x_bound(1),x_bound(2),4))'; // Points of experiment
YExp=sin(X);// Response values
noise=0.0000001;theta=1;
[kmodel] =km(X,YExp,0,'gaussian',theta,noise);// creates kriging model  (constant trend)
Xtest=(linspace(x_bound(1),x_bound(2),100))'; // 100 point test sample
[Sim1]=SimCondGaussian(Xtest,kmodel,50);
scf;
plot(Xtest,Sim1,'k'); // simulations

See also

Authors

Bibliography

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