.decomp_quad

Compute sgn, scale, M such that \(P = sgn * scale * dot(M, t(M))\).

An object-oriented modeling language for disciplined
convex programming (DCP) as described in Fu, Narasimhan, and Boyd
(2020, <doi:10.18637/jss.v094.i14>). It allows the user to
formulate convex optimization problems in a natural way following
mathematical convention and DCP rules. The system analyzes the
problem, verifies its convexity, converts it into a canonical
form, and hands it off to an appropriate solver to obtain the
solution. Interfaces to solvers on CRAN and elsewhere are
provided, both commercial and open source.

Anqi Fu

CVXR

Disciplined Convex Optimization

Balasubramanian Narasimhan

David W Kang

Steven Diamond

John Miller

Stephen Boyd

Paul Kunsberg Rosenfield

.decomp_quad function

<dl><dt>P</dt>
<dd>A real symmetric positive or negative (semi)definite input matrix</dd>
<dt>cond</dt>
<dd>Cutoff for small eigenvalues. Singular values smaller than rcond * largest_eigenvalue are considered negligible.</dd>
<dt>rcond</dt>
<dd>Cutoff for small eigenvalues. Singular values smaller than rcond * largest_eigenvalue are considered negligible.</dd></dl>

Arguments

Compute a Matrix Decomposition. — .decomp_quad

<dl>

<dt>P</dt>
<dd>A real symmetric positive or negative (semi)definite input matrix</dd>


<dt>cond</dt>
<dd>Cutoff for small eigenvalues. Singular values smaller than rcond * largest_eigenvalue are considered negligible.</dd>


<dt>rcond</dt>
<dd>Cutoff for small eigenvalues. Singular values smaller than rcond * largest_eigenvalue are considered negligible.</dd>

</dl>

.decomp_quad: Compute a Matrix Decomposition.

Description

Usage

Value

Arguments