The Bidiagonal class is used to creates a bidiagonal matrix for matrix 'a'.
The Cholesky class provides a method to factor symmetric positive definite
matrices 'a' into 'l * l.
The Eigen trait defines constants used by classes and objects the Eigen group.
The Eigenvalue class is used to find the eigenvalues of an 'n' by 'n' matrix
'a' using an iterative technique that applies similarity transformations to
convert 'a' into an upper triangular matrix, so that the eigenvalues appear
along the diagonal.
The EigenvalueSym class is used to find the eigenvalues of an 'n' by 'n'
symmetric matrix 'a' using an iterative technique, the Symmetric QR Algorithm.
The Eigenvector class is used to find the eigenvectors of an 'n' by 'n' matrix
'a' by solving equations of the form
The Hessenburg class is used to reduce, via similarity transformations, an
'n' by 'n' matrix 'a' to Hessenburg form 'h', where all elements two below the
main diagonal are zero (or close to zero).
The HouseholderT class performs a Householder Tridiagonalization on a
symmetric matrix.
The Matric trait specifies the operations to be defined by three concrete
implemeting classes: MatrixC, SparseMatrixC and SymTriMatrixC.
The Matrir trait specifies the operations to be defined by three concrete
implemeting classes: MatrixR, SparseMatrixR and SymTriMatrixR.
The Matrix trait specifies the operations to be defined by four concrete
implemeting classes: MatrixD, ParMatrixD, SparseMatrixD and SymTriMatrixD.
The MatrixC class stores and operates on Numeric Matrices of type Complex.
The MatrixD class stores and operates on Numeric Matrices of type Double.
The MatrixR class stores and operates on Numeric Matrices of type Rational.
The ParMatrixD class stores and operates parallel on Numeric Matrices of type
Double.
The ParSparseMatrixD class stores and operates on Matrices of Doubles.
The QRDecomp class is used to decompose an 'm' by 'n' matrix 'a' into an
orthogonal 'm' by 'n' matrix 'q' and an 'n' by 'n' right upper triangular
matrix 'r' such that 'a = q * r'.
The SVD class is used to compute the Singlar Value Decomposition (SVD) of
matrix 'a' using the Golub-Kahan-Reinsch Algorithm.
The SVDecomp class performs Single Value Decompositions (SVDs) using the
Eigen class.
The SparseMatrixC class stores and operates on Matrices of Complex numbers.
The SparseMatrixD class stores and operates on Matrices of Doubles.
The SymTriMatrixC class stores and operates on symmetric tridiagonal matrices.
The SymTriMatrixD class stores and operates on symmetric tridiagonal matrices.
The VectorC class stores and operates on Numeric Vectors of base type Complex.
The VectorD class stores and operates on Numeric Vectors of base type Double.
The VectorR class stores and operates on Numeric Vectors of base type Rational.
The BidiagonalTest object is used to test the Bidiagonal class.
The CholeskyTest object is used to test the Cholesky class.
The Eigen2 object provides simple methods for computing eigenvalues and
eigenvectors for 2-by-2 matrices.
The Eigen2Test is used to test the Eigen object.
The EigenTest object is used to test the all the classes used in computing
Eigenvalues and Eigenvectors for the non-symmetric/general case.
The Givens objects has methods for determinng values 'c = cos(theta)' and
's = sin(theta) for Givens rotation matrices as well as methods for applying
Givens rotations.
The GivensTest object tests the Givens object by using two rotations to
turn matrix 'a' into an upper triangular matrix, clearing positions (1, 0)
and (2, 1).
The Householder object provides methods to compute Householder vectors and
reflector matrices.
The HouseholderTest object is used to test Householder object.
The MatrixC companion object provides operations for MatrixC that don't require 'this' (like static methods in Java).
The MatrixCTest object tests the operations provided by MatrixC class.
The MatrixD companion object provides operations for MatrixD that don't require
'this' (like static methods in Java).
The MatrixDTest object tests the operations provided by MatrixD class.
The MatrixR companion object provides operations for MatrixR that don't require 'this' (like static methods in Java).
The MatrixRTest object tests the operations provided by MatrixR class.
The ParMatrixD companion object provides operations for ParMatrixD that don't
require 'this' (like static methods in Java).
The ParMatrixDTest object tests the operations provided by ParMatrixD class.
The ParSparseMatrixDTest object is used to test the ParSparseMatrixD class.
The QRDecompTest object is used to test the QRDecomp class.
The SVD companion object.
The SVDTest object is used to test the SVD class starting with a matrix that
is already bidiagonalized and gives eigenvalues of 28, 18 for the first step.
The SVDTest2 object is used to test the SVD class starting with a general
matrix.
The SVDTest3 object is used to test the SVD companion object.
The SVDecompTest object is used to test the SVDecomp class.
The SparseMatrixC objecxt is the companion object for the SparseMatrixC class.
The SparseMatrixCTest object is used to test the SparseMatrixC class.
The SparseMatrixD object is the companion object for the SparseMatrixD class.
The SparseMatrixDTest object is used to test the SparseMatrixD class.
The SymTriMatrixCTest object is used to test the SymTriMatrixC class.
The SymTriMatrixDTest object is used to test the SymTriMatrixD class.
The SymmetricQRstep object performs a symmetric QR step with a Wilkinson shift.
The VectorC object is the companion object for VectorC class.
The VectorCTest object tests the operations provided by VectorC class.
The VectorD object is the companion object for the VectorD class.
The VectorDTest object tests the operations provided by VectorD.
The VectorR object is the companion object for Vector class.
The VectorRTest object tests the operations provided by VectorR class.
The linalgebra package contains classes, traits and objects for linear algebra, including vectors and matrices for real and complex numbers.