rtmpinv: Tabular Matrix Problems via Pseudoinverse Estimation
The Tabular Matrix Problems via Pseudoinverse Estimation (TMPinv)
is a two-stage estimation method that reformulates structured table-based
systems - such as allocation problems, transaction matrices, and
input-output tables - as structured least-squares problems. Based on the
Convex Least Squares Programming (CLSP) framework, TMPinv solves systems
with row and column constraints, block structure, and optionally reduced
dimensionality by (1) constructing a canonical constraint form and applying
a pseudoinverse-based projection, followed by (2) a convex-programming
refinement stage to improve fit, coherence, and regularization (e.g., via
Lasso, Ridge, or Elastic Net).
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=rtmpinv
to link to this page.