Test matrix for positive definiteness
This function returns TRUE if the argument, a square symmetric real matrix x, is positive definite.
is.positive.definite(x, tol=1e-8)
x |
a matrix |
tol |
a numeric tolerance level |
For a positive definite matrix, the eigenvalues should be positive. The R function eigen
is used to compute the eigenvalues. If any of the eigenvalues in absolute value is less than the
given tolerance, that eigenvalue is replaced with zero. If any of the eigenvalues is less than or equal to zero,
then the matrix is not positive definite. Otherwise, the matrix is declared to be positive definite.
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.positive.definite( 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.positive.definite( 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.positive.definite( 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.positive.definite( 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.positive.definite( 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.positive.definite( E )
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