Project a precision matrix onto a fixed graph (constrained estimate)

Given a precision matrix (K) and a fixed undirected graph (G), returns the precision matrix constrained to the graph's structure, so that entries at non-edges are (numerically) zero. Uses the node-wise regression algorithm.

Usage

constrain_precision_to_graph(K, G, tol = 1e-06, itermax = 1000)

Arguments

K

A \(p \times p\) symmetric positive-definite precision matrix.

G

A \(p \times p\) symmetric adjacency matrix with 0/1 entries; the zero pattern defines the conditional-independence constraints.

tol

Convergence tolerance for the iterative solver.

itermax

Maximum number of iterations.

Value

A \(p \times p\) precision matrix with zeros at the non-edges of G.