rtmpinvi: Interactive Tabular Matrix Problems via Pseudoinverse Estimation
Provides an interactive wrapper for the 'tmpinv()' function from
the 'rtmpinv' package with options extending its functionality to pre-
and post-estimation processing and streamlined incorporation of prior cell
information. 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).
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