GaussianProcessNormal::GaussianProcessNormal(size_t dim,
bopt_params params):
HierarchicalGaussianProcess(dim,params),
mSigma(params.sigma_s),
mW0(params.mean.n_coef), mInvVarW(params.mean.n_coef),
mD(params.mean.n_coef,params.mean.n_coef)
{
mW0 = utils::array2vector(params.mean.coef_mean,params.mean.n_coef);
for (size_t ii = 0; ii < params.mean.n_coef; ++ii)
{
double varii = params.mean.coef_std[ii] * params.mean.coef_std[ii];
mInvVarW(ii) = 1/varii;
}
d_ = new GaussianDistribution();
} // Constructor
StudentTProcessNIG::StudentTProcessNIG(size_t dim, bopt_params params,
const Dataset& data,
MeanModel& mean, randEngine& eng):
HierarchicalGaussianProcess(dim,params,data, mean, eng),
mAlpha(params.alpha), mBeta (params.beta),
mW0(params.mean.n_coef), mInvVarW(params.mean.n_coef),
mD(params.mean.n_coef,params.mean.n_coef)
{
mW0 = utils::array2vector(params.mean.coef_mean,params.mean.n_coef);
for (size_t ii = 0; ii < params.mean.n_coef; ++ii)
{
double varii = params.mean.coef_std[ii] * params.mean.coef_std[ii];
mInvVarW(ii) = 1/varii;
}
d_ = new StudentTDistribution(eng);
} // Constructor
