/** * Premultiplies the matrix by the vector "this" * @param matrix * Matrix to premultiply by "this", must have the same number of rows as * the dimensionality of "this" * @return * Vector of dimension equal to the number of columns of "matrix" */ public Vector times( AbstractMTJMatrix matrix ) { int N = matrix.getNumColumns(); DenseVector retval = new DenseVector( N ); matrix.getInternalMatrix().transMult( this.getInternalVector(), retval.getInternalVector() ); return retval; }
/** * Premultiplies the matrix by the vector "this" * @param matrix * Matrix to premultiply by "this", must have the same number of rows as * the dimensionality of "this" * @return * Vector of dimension equal to the number of columns of "matrix" */ public Vector times( AbstractMTJMatrix matrix ) { int N = matrix.getNumColumns(); DenseVector retval = new DenseVector( N ); matrix.getInternalMatrix().transMult( this.getInternalVector(), retval.getInternalVector() ); return retval; }
/** * Premultiplies the matrix by the vector "this" * @param matrix * Matrix to premultiply by "this", must have the same number of rows as * the dimensionality of "this" * @return * Vector of dimension equal to the number of columns of "matrix" */ public Vector times( AbstractMTJMatrix matrix ) { int N = matrix.getNumColumns(); DenseVector retval = new DenseVector( N ); matrix.getInternalMatrix().transMult( this.getInternalVector(), retval.getInternalVector() ); return retval; }
Matrix R = new UpperTriangDenseMatrix(qrp.getR(), false); Matrix P = qrp.getP(); DenseVector cPlusd = (DenseVector)Q.transMult(dependent, new DenseVector(dependent.size())); dependent = null; Vector c = new DenseVector(Arrays.copyOf(cPlusd.getData(), numAttributes));
Matrix R = new UpperTriangDenseMatrix(qrp.getR(), false); Matrix P = qrp.getP(); DenseVector cPlusd = (DenseVector)Q.transMult(dependent, new DenseVector(dependent.size())); dependent = null; Vector c = new DenseVector(Arrays.copyOf(cPlusd.getData(), numAttributes));
A.transMult(ptilde, qtilde);
A.transMult(ptilde, qtilde);