Test matrix for positive indefiniteness
This function returns TRUE if the argument, a square symmetric real matrix x, is indefinite. That is, the matrix has both positive and negative eigenvalues.
is.indefinite(x, tol=1e-8)
x |
a matrix |
tol |
a numeric tolerance level |
For an indefinite matrix, the matrix should positive and negative eigenvalues. The R function eigen
is used to compute the eigenvalues. If any of the eigenvalues is absolute value is less than the
given tolerance, that eigenvalue is replaced with zero. If the matrix has both positive and
negative eigenvalues, it is declared to be indefinite.
TRUE or FALSE.
Frederick Novomestky fnovomes@poly.edu
Bellman, R. (1987). Matrix Analysis, Second edition, Classics in Applied Mathematics, Society for Industrial and Applied Mathematics.
### ### identity matrix is always positive definite ### I <- diag( 1, 3 ) is.indefinite( I ) ### ### positive definite matrix ### eigenvalues are 3.4142136 2.0000000 0.585786 ### A <- matrix( c( 2, -1, 0, -1, 2, -1, 0, -1, 2 ), nrow=3, byrow=TRUE ) is.indefinite( A ) ### ### positive semi-defnite matrix ### eigenvalues are 4.732051 1.267949 8.881784e-16 ### B <- matrix( c( 2, -1, 2, -1, 2, -1, 2, -1, 2 ), nrow=3, byrow=TRUE ) is.indefinite( B ) ### ### negative definite matrix ### eigenvalues are -0.5857864 -2.0000000 -3.4142136 ### C <- matrix( c( -2, 1, 0, 1, -2, 1, 0, 1, -2 ), nrow=3, byrow=TRUE ) is.indefinite( C ) ### ### negative semi-definite matrix ### eigenvalues are 1.894210e-16 -1.267949 -4.732051 ### D <- matrix( c( -2, 1, -2, 1, -2, 1, -2, 1, -2 ), nrow=3, byrow=TRUE ) is.indefinite( D ) ### ### indefinite matrix ### eigenvalues are 3.828427 1.000000 -1.828427 ### E <- matrix( c( 1, 2, 0, 2, 1, 2, 0, 2, 1 ), nrow=3, byrow=TRUE ) is.indefinite( E )
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