MDArray<double> Shrinkage::combine(MDArray<double> target,MDArray<double> MLE,double lambda)
{
assert(target.get_shape() == MLE.get_shape());
// assert(lambda>=0 && lambda<=1);
lambda = std::max(lambda, 0.0);
lambda = std::min(lambda, 1.0);
return add_matrices(mult_num_to_matrix(target,lambda),mult_num_to_matrix(MLE,1-lambda));
}
void ParentMap::set(uint h, MDArray<double> & v) {
vector<uint> & v1 = indices[h];
uint i = v1.back();
assert(v.get_shape().size() == 1);
uint dim = v.get_shape().front();
uint k = 0;
for (uint j = i; j < i + dim; j++, k++) {
*(seq[j]) = v[k];
}
}
Shrinkage::Shrinkage(MDArray<double> data, MDArray<double> MLE)
{
N=data.get_shape()[0];
P=data.get_shape()[1];
assert(MLE.get_shape()[0]==P && MLE.get_shape()[1]==P);
this->data=data;
wk=wk_StDM=vec(N,P,P);
S_MLE=vec(P,P);
StDM=vec(N,P);
set_S_MLE(MLE);
}
Shrinkage::Shrinkage(MDArray<double> data)
{
N=data.get_shape()[0];
P=data.get_shape()[1];
this->data=data;
wk=wk_StDM=vec(N,P,P);
S_MLE=vec(P,P);
StDM=vec(N,P);
generate_MLE();
}
void MultinomialDensities::set_parameters(MDArray<double> & cpd)
{
// Check cpd is right shape
vector<uint> shape = cpd.get_shape();
assert(shape[1] == dim);
this->cpd = cpd;
this->cpd.normalize();
// make new MultinomialDensity objects
_create_densities();
}
void Shrinkage::generate_wk(MDArray<double> mat,int SDM_type)
{
int n=mat.get_shape()[0];
int p=mat.get_shape()[1];
vector<uint> index;
double sum,term1,term2;
MDArray<double> sub_means(get_sub_means(mat));
for(int i=0;i<p;i++)
for(int j=0;j<p;j++){
sum=0;
for(int k=0;k<n;k++){
term1=mat.get(k,i)-sub_means[i];
term2=mat.get(k,j)-sub_means[j];
index=vec((uint)k, (uint)i, (uint)j);
if(SDM_type)
wk_StDM[index]=term1*term2;
else
wk[index]=term1*term2;
}
}
}
