Inversion and the change of variables on the positive-definite cone #
Matrix inversion is a self-map TauCeti.symmetricInv of the symmetric subspace, and an
involution of the positive-definite cone. Its derivative at an invertible A is H ↦ -A⁻¹ H A⁻¹,
that is, minus the congruence by A⁻¹, whose determinant
Matrix.det_symmetricCongruenceLinearMap already computes. Hence the absolute Jacobian of
inversion is |det A| ^ (-(p + 1)), and TauCeti.map_symmetricInv_symmetricLebesgue records the
resulting change of variables: inversion carries TauCeti.symmetricLebesgue restricted to the cone
to the same restriction weighted by (det B) ^ (-(p + 1)).
This is the change of variables behind the inverse-Wishart density: it reads the density of the image of a Wishart law under inversion off the density of the law itself.
Main declarations #
TauCeti.symmetricInv— matrix inversion as a self-map of the symmetric subspace.TauCeti.bijOn_symmetricInv— inversion is a bijection of the positive-definite cone onto itself.TauCeti.measurable_symmetricInv— inversion is measurable.TauCeti.hasFDerivAt_symmetricInv— its derivative at an invertible matrix is minus the congruence by the inverse.TauCeti.abs_det_fderiv_symmetricInv— the absolute Jacobian of inversion.TauCeti.map_symmetricInv_symmetricLebesgue— the change of variables on the positive-definite cone.
References #
- R. J. Muirhead, Aspects of Multivariate Statistical Theory, Wiley, 1982, chapter 2 (the Jacobian of symmetric inversion and the inverse-Wishart density).
Inversion on the symmetric subspace #
Matrix inversion as a self-map of the symmetric subspace. Mathlib's totalized inverse is zero on singular matrices and that value is kept here; on the positive-definite cone, where the Wishart laws live, the map is an involution.
Instances For
The underlying matrix of the inverse is the inverse of the underlying matrix.
Inversion is an involution at an invertible matrix.
Inversion is a bijection of the positive-definite cone onto itself: it maps the cone into itself and is its own inverse there.
Measurability of inversion #
Inversion is measurable, being a rational expression in the entries: Mathlib's totalized
inverse is (det A)⁻¹ • adjugate A everywhere.
The derivative of inversion #
The derivative of inversion at an invertible symmetric matrix A is H ↦ -A⁻¹ H A⁻¹, minus
the congruence by A⁻¹.
The change of variables #
The change of variables for inversion on the positive-definite cone. The pushforward of
TauCeti.symmetricLebesgue restricted to the cone under inversion is the same restriction
weighted by (det B) ^ (-(p + 1)). This is what turns the Wishart density into the
inverse-Wishart density.