Introduction | Installation | Example: classo | Example: cglasso | Example: Sparse Spectral Precision Matrix Estimation | Step 1 — Generate a multivariate Gaussian white noise process: | Step 2 — Compute the DFT and smoothed periodogram: | Step 3 — Estimate sparse spectral precision matrix via \texttt{cglasso}: | Step 4 — Visualize the estimated spectral precision matrix: | Step 5 — Compare to the true precision matrix:

Introduction | Background | Spectral density and the DFT | The CGLASSO and deCGLASSO estimators | Step 1 — Generate a multivariate white noise process | Step 2 — Bandwidth selection via GCV | Step 3 — Compute the DFT and smoothed periodogram | Step 4 — Fit CGLASSO and compute the deCGLASSO estimator | Step 5 — Estimate the asymptotic variance | Step 6 — Entry-wise tests and confidence regions | Step 7 — FDR-controlled support recovery | Summary of functions | References