el_sem_naive::el_sem_naive(SEXP weights_r, SEXP y_r, SEXP omega_r, SEXP b_r , SEXP dual_r, int meanEst)
{
mat y = as<arma::mat>(y_r);
n_ = y.n_cols;
v_ = y.n_rows;
counter_ = 0;
conv_crit_ = 1.0;
//find appropriate spots to put in b_weights_r and omega_weights so that we can build sigma
uvec b_spots = find(as<arma::mat>(b_r));
uvec omega_spots = arma::find(trimatl(as<arma::mat>(omega_r)));
vec weights = as<arma::vec>(weights_r);
mat omega_weights(v_, v_, fill::zeros);
mat b_weights(v_, v_, fill::zeros);
vec means = vec(v_, fill::zeros); //non-zero means
if(meanEst){
means = as<arma::vec>(weights_r).head(v_);
b_weights.elem(b_spots) = as<arma::vec>(weights_r).subvec(v_, v_ + b_spots.n_elem - 1);
omega_weights.elem(omega_spots) = weights.subvec(v_ + b_spots.n_elem, v_ + b_spots.n_elem + omega_spots.n_elem - 1);
omega_weights = symmatl(omega_weights);
} else {
b_weights.elem(b_spots) = weights.subvec(0, b_spots.n_elem - 1);
omega_weights.elem(omega_spots) = weights.subvec(b_spots.n_elem, b_spots.n_elem + omega_spots.n_elem - 1);
omega_weights = symmatl(omega_weights);
}
sigma_ = solve( (eye(v_, v_) - b_weights), solve( eye(v_, v_) - b_weights, omega_weights).t());
dual_ = as<arma::vec>(dual_r);
//
constraints_ = mat(v_ + (v_ *(v_ + 1) )/ 2, n_);
constraints_.rows(0, v_ - 1) = (eye(v_, v_) - b_weights) * y;
if(meanEst) {
constraints_.rows(0, v_ - 1).each_col() -= means;
}
int i,j,k;
k = v_;
for(i = 0; i < v_; i++) {
for(j = 0; j <= i; j++ ) {
constraints_.row(k) = (y.row(i) % y.row(j)) - sigma_(i,j);
k++;
}
}
d_ = (constraints_.t() * dual_) + 1.0;
}
inline
bool
glue_solve_tri::apply(Mat<eT>& out, const Base<eT,T1>& A_expr, const Base<eT,T2>& B_expr, const uword flags)
{
arma_extra_debug_sigprint();
const bool fast = bool(flags & solve_opts::flag_fast );
const bool equilibrate = bool(flags & solve_opts::flag_equilibrate);
const bool no_approx = bool(flags & solve_opts::flag_no_approx );
const bool triu = bool(flags & solve_opts::flag_triu );
const bool tril = bool(flags & solve_opts::flag_tril );
arma_extra_debug_print("glue_solve_tri::apply(): enabled flags:");
if(fast ) { arma_extra_debug_print("fast"); }
if(equilibrate) { arma_extra_debug_print("equilibrate"); }
if(no_approx ) { arma_extra_debug_print("no_approx"); }
if(triu ) { arma_extra_debug_print("triu"); }
if(tril ) { arma_extra_debug_print("tril"); }
bool status = false;
if(equilibrate) { arma_debug_warn("solve(): option 'equilibrate' ignored for triangular matrices"); }
const unwrap_check<T1> U(A_expr.get_ref(), out);
const Mat<eT>& A = U.M;
arma_debug_check( (A.is_square() == false), "solve(): matrix marked as triangular must be square sized" );
const uword layout = (triu) ? uword(0) : uword(1);
status = auxlib::solve_tri(out, A, B_expr.get_ref(), layout); // A is not modified
if( (status == false) && (no_approx == false) )
{
arma_extra_debug_print("glue_solve_tri::apply(): solving rank deficient system");
arma_debug_warn("solve(): system seems singular; attempting approx solution");
Mat<eT> triA = (triu) ? trimatu( A_expr.get_ref() ) : trimatl( A_expr.get_ref() );
status = auxlib::solve_approx_svd(out, triA, B_expr.get_ref()); // triA is overwritten
}
if(status == false) { out.reset(); }
return status;
}
int MCMCPkPg::sampleZ( PkPgModel& model, PkPgResult& Result ){
//zeros<mat>( model.N, model.Q ); // temporaly sample Z_ig - mu_ig
mat RO = Result.Rho * Result.Otheta;
mat RORt = RO * Result.Rho.t();
mat SZi = Result.Osnp + RORt;
mat cZU = chol( SZi );
//std::cout <<"g0"<<std::endl;
uvec aidx( 1 );
umat bidx_temp( model.Q, 1 );
for( size_t g = 0; g < model.Q; g++ ){
bidx_temp( g, 0 ) = g;
}
mat clogt = ( Result.logTheta- Result.XBetaPk );
mat tempMz0 = Result.Osnp * Result.XBetaPg.t() + RO *clogt.t();
mat v0 = solve( trimatl( trans( cZU ) ), tempMz0 );
mat mz0 = trans(solve( trimatu( cZU ), v0 ) );
//std::cout <<"g"<<std::endl;
for( size_t i = 0; i < model.N; i++ ){
vec z = Result.Z.row(i).t();
for( size_t j = 0; j < model.Q; j++ ){
//std::cout <<"g2"<<std::endl;
// mat tempMz = Result.Osnp * Result.XBetaPg.row(i).t() + RO *clogt.row(i).t() ;
// mat v = solve( trimatl( trans( cZU ) ), tempMz );
// vec mz = solve( trimatu( cZU ), v ) ;
vec mz = mz0.row(i).t();
aidx( 0 ) = j;
//mz.print("mz");
//std::cout <<"g1"<<std::endl;
umat bidxt = bidx_temp;
//std::cout <<"g2"<<std::endl;
bidxt.shed_row( j );
//std::cout <<"g3"<<std::endl;
uvec bidx = bidxt.col( 0 );//conv_to< uvec >::from( bidxt);
//std::cout <<"g4"<<std::endl;
double sdz1 =pow( SZi( j, j ), - 0.5 );
// std::cout <<"g5"<<std::endl;
double mzc1 = as_scalar( SZi.submat(aidx,bidx)*(z.elem(bidx)-mz.elem(bidx)));
double mzc = mzc1/SZi( j, j );
/// std::cout <<"g6"<<std::endl;
z( j ) = ZgivenW( model.W( i, j ),mzc, sdz1 );
// std::cout <<"mz( i, j )"<<mz( j )<<std::endl;
// std::cout <<"z( i, j )"<<z( i, j )<<std::endl;
// std::cout <<"g3"<<std::endl;
Result.Z( i, j ) = z( j ) ;
// std::cout <<"g10"<<std::endl;
}
}
// for( size_t i = 0; i < model.N; i++ ){
// int Qidx = model.Q - 1;
// double sdz1 = cZU( Qidx, Qidx );//1.0 / cZU( Qidx, Qidx );
// double mzc1 = mz( i, Qidx);//double mzc1 = mz( i, Qidx );
// z( i, Qidx ) = ZgivenW(model.W( i, Qidx ),mzc1, sdz1 );
// for( int g = ( model.Q - 1 ); g >= 0 ; g-- ){
// double mzc = 0;//double mzc = mz( i, g );
// for( size_t j = g + 1; j < model.Q ; j++ ){
// //mzc -= ( z( i, j ) - mz( i, j ) ) * cZU( g, j )/cZU( g, g );
// mzc -= ( z( i, j ) - mz( i, j ) ) * cZU( g, j );//cZU( g, g )
// } // j
// double sdz = cZU( g, g ) ;//1.0 / cZU( g, g ) ;
// z( i, g ) = ZgivenW( model.W( i, g ), mzc, sdz ) + mz( i, g );
// Result.Z( i, g ) = z( i, g ) ;
// }//g
// }//i
Result.ZtZ = Result.Z.t() * Result.Z; // update ZtZ also
Result.ZRho= Result.Z * Result.Rho;
return 0;
}
