Problem with implement a 4-D Gaussian Processes Regression through GPML

Question

I refer to the link https://stats.stackexchange.com/questions/105516/how-to-implement-a-2-d-gaussian-processes-regression-through-gpml-matlab and create a 2-d Gaussian Process regression. I want to create a 4-d Gaussian Process regression, however the 'meshgrid' only allows 3 inputs([X,Y,Z] = meshgrid(x,y,z)); how do I add another input into meshgrid?

The 3-d code is like:

X1train = linspace(-4.5,4.5,10);
X2train = linspace(-4.5,4.5,10);
X3train = linspace(-4.5,4.5,10);
X = [X1train' X2train' X3train'];
Y = [X1train + X2train + X3train]';

%Testdata
[Xtest1, Xtest2, Xtest3] = meshgrid(-4.5:0.1:4.5, -4.5:0.1:4.5, -4.5:0.1:4.5);
 Xtest = [Xtest1(:) Xtest2(:) Xtest3(:)];

% implement regression 
[ymu ys2 fmu fs2] = gp(hyp, @infExact, [], covfunc, likfunc, X, Y, Xtest);

If I create an X4train, that means I need an Xtest4, how do I add Xtest4 into meshgrid?

The GPML code is from http://www.gaussianprocess.org/gpml/code/matlab/doc/

Answer 1

You may create n- dimensional grids using ndgrid, but please keep in mind that it does not directly create the same output as meshgrid, you have to convert it first. (How to do that is also explained in the documentation)