Define an SVD problem.

Usage

svd_problem(A, domain = NULL, codomain = NULL, target = largest())

Arguments

A: Matrix or operator defining the rectangular linear map.
domain: Optional domain-space descriptor.
codomain: Optional codomain-space descriptor.
target: Eigencore singular-value target descriptor.

Value

An eigencore_svd_problem object containing the operator, domain and codomain descriptors, and singular-value target consumed by plan_solver() and solve().

Examples

set.seed(1)
X <- matrix(rnorm(40), 8, 5)
S <- svd_problem(X, target = largest())
fit <- solve(S, rank = 2)
values(fit)
#> [1] 3.309631 3.044806