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tfb_cholesky_outer_product

Computesg(X) = X @ X.T where X is lower-triangular, positive-diagonal matrix


Description

Note: the upper-triangular part of X is ignored (whether or not its zero).

Usage

tfb_cholesky_outer_product(
  validate_args = FALSE,
  name = "cholesky_outer_product"
)

Arguments

validate_args

Logical, default FALSE. Whether to validate input with asserts. If validate_args is FALSE, and the inputs are invalid, correct behavior is not guaranteed.

name

name prefixed to Ops created by this class.

Details

The surjectivity of g as a map from the set of n x n positive-diagonal lower-triangular matrices to the set of SPD matrices follows immediately from executing the Cholesky factorization algorithm on an SPD matrix A to produce a positive-diagonal lower-triangular matrix L such that A = L @ L.T.

To prove the injectivity of g, suppose that L_1 and L_2 are lower-triangular with positive diagonals and satisfy A = L_1 @ L_1.T = L_2 @ L_2.T. Then inv(L_1) @ A @ inv(L_1).T = [inv(L_1) @ L_2] @ [inv(L_1) @ L_2].T = I. Setting L_3 := inv(L_1) @ L_2, that L_3 is a positive-diagonal lower-triangular matrix follows from inv(L_1) being positive-diagonal lower-triangular (which follows from the diagonal of a triangular matrix being its spectrum), and that the product of two positive-diagonal lower-triangular matrices is another positive-diagonal lower-triangular matrix. A simple inductive argument (proceeding one column of L_3 at a time) shows that, if I = L_3 @ L_3.T, with L_3 being lower-triangular with positive- diagonal, then L_3 = I. Thus, L_1 = L_2, proving injectivity of g.

Value

a bijector instance.

See Also


tfprobability

Interface to 'TensorFlow Probability'

v0.11.0.0
Apache License (>= 2.0)
Authors
Sigrid Keydana [aut, cre], Daniel Falbel [ctb], Kevin Kuo [ctb] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Initial release

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