Package: cxreg 1.1.2

Younghoon Kim

cxreg: Complex-Valued Lasso and Complex-Valued Graphical Lasso

Implements 'glmnet'-style complex-valued lasso (CLASSO) and complex-valued graphical lasso (CGLASSO) via a pathwise coordinate descent algorithm for complex-valued parameters, using an isomorphism between complex numbers and 2x2 orthogonal matrices. Also provides a full inference pipeline for high-dimensional sparse spectral precision matrices, including data-driven bandwidth selection, one-step debiasing, asymptotic variance estimation, entry-wise confidence regions, and FDR-controlled hypothesis testing. Supporting tools for cross-validation, simulation, coefficient extraction, and plotting are included. See Deb, Kuceyeski, and Basu (2024) <doi:10.48550/arXiv.2401.11128> and Deb, Kim, and Basu (2026) <doi:10.48550/arXiv.2606.07986>.

Authors:Younghoon Kim [aut, cre], Navonil Deb [aut], Sumanta Basu [aut]

cxreg_1.1.2.tar.gz
cxreg_1.1.2.tar.gz(r-4.7-arm64)cxreg_1.1.2.tar.gz(r-4.7-x86_64)cxreg_1.1.2.tar.gz(r-4.6-arm64)cxreg_1.1.2.tar.gz(r-4.6-x86_64)
cxreg_1.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cxreg/json (API)

# Install 'cxreg' in R:

install.packages('cxreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

cglasso_example - Example data for cglasso
classo_example - Example data for classo

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.00 score 6 scripts 3 downloads 17 exports 15 dependencies

Last updated from:54520d5598. Checks:4 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	213
linux-devel-x86_64	WARNING	222
source / vignettes	OK	222
linux-release-arm64	WARNING	177
linux-release-x86_64	WARNING	199
wasm-release	OK	177

Exports:buildPredmat cglasso classo classo.control coef.classo cv.classo decglasso dft.all dft.j fhat_at predict.classo print.classo print.cv.classo select_m spec.fdr spec.test var.cov

Dependencies:codetools dotCall64 fields foreach gdata gtools iterators lattice maps Matrix mvtnorm RColorBrewer Rcpp spam viridisLite

An Introduction to cxreg

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:

Rendered fromcxreg.Rmdusingknitr::rmarkdown

Last update: 2026-07-05
Started: 2026-07-05

Help page	Topics
Complex-valued Lasso, graphical Lasso, and spectral inference	cxreg-package
Build Prediction Matrix	buildPredmat buildPredmat.default
fit a complex-valued graphical lasso	cglasso
Example data for cglasso	cglasso_example
fit a complex-valued graphical Lasso for a path of lambda values	cglasso.path
fit a complex-valued lasso	classo
Example data for classo	classo_example
Internal classo parameters	classo.control
fit a complex-valued lasso for a path of lambda values	classo.path
Extract coefficients from a classo object	coef.classo predict.classo
Extract coefficients from a cv.classo object	coef.cv.classo
Cross-validation for classo	cv.classo
Simulated data for the cxreg vignette	cxreg x y
Debias the cglasso estimator	decglasso
Discrete Fourier Transform of matrix X	dft.all
Discrete Fourier Transform of matrix X at a fixed frequency omega_j	dft.j
Extract the family from a classo object	family.classo family.classofit family.cv.classo
Smoothed periodogram at a fixed frequency	fhat_at
Plot heatmap from a "cglasso" object	plot.cglasso
plot coefficients from a "classo" object	plot.classo
plot the cross-validation curve produced by cv.classo	plot.cv.classo
Make predictions from a "cv.classo" object	predict.cv.classo
print a classo object	print.classo
print a cross-validated classo object	print.cv.classo
Select the optimal bandwidth 'm' for spectral density estimation	select_m
FDR-controlled hypothesis testing for spectral precision matrix entries	spec.fdr
Confidence regions and test statistics for spectral precision matrix entries	spec.test
Variance-covariance estimation for the debiased spectral precision matrix	var.cov

Package: cxreg 1.1.2

cxreg: Complex-Valued Lasso and Complex-Valued Graphical Lasso

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)