Gaussian process regression - how to fit a basis function but not other parameters

I'm doing Gaussian process regression with the fitrgp function and want to manually control some parameters such as the kernel parameters and the noise parameter, but automatically fit a basis function (e.g. 'linear').

However, it seems that to fit a basis function the FitMethod parameter cannot be 'none':

1. Manual parameter settings (no parameter fitting) but no basis function

gpr_model = fitrgp(x_d, y_d, ...
    'KernelParameters', [1.5; 1], ...
    'Sigma', 0.1, ...
    'FitMethod', 'none' ...
    );

2. To fit the basis function I can't have FitMethod set to 'none' ('exact' is the default) but then it ignores my parameter values:

gpr_model = fitrgp(x_d, y_d, ...
    'KernelParameters', [1.5; 1], ...
    'Sigma', 0.1, ...
    'BasisFunction', 'linear' ...
    );

3. If I set FitMethod to none, it ignores the basis function:

gpr_model = fitrgp(x_d, y_d, ...
    'KernelParameters', [1.5; 1], ...
    'Sigma', 0.1, ...
    'BasisFunction', 'linear', ...
    'FitMethod', 'none' ...
);

(same a Fig. 1).

Is there a way to fit a basis function but not the other parameters?

[Bill Tubbs]

As a follow-up, I see that fitrgp has a ConstantSigma argument. Also there is a SigmaLowerBound. Is there any way of fixing or constraining the kernel parameters? (I can't see one). That would solve my problem I think.