missoNet: Missingness in Multi-Task Regression with Network Estimation

Efficient procedures for fitting the conditional graphical lasso models linking a set of predictor variables to a set of response variables (or tasks), when the response data may contain missing values. 'missoNet' simultaneously estimates the predictor coefficients for all tasks by leveraging information from one another, in order to provide more accurate predictions in comparison to modeling them individually. Meanwhile, 'missoNet' is able to estimate the response network structure influenced by conditioning predictor variables in a L1-regularized conditional Gaussian graphical model. In contrast to most penalized multi-task regression (conditional graphical lasso) methods, 'missoNet' has the capability of obtaining estimates even when the response data is corrupted by missing values. The method automatically enjoys the theoretical and computational benefits of convexity, and returns solutions that are comparable/close to the estimates without any missing values. The package also includes auxiliary functions for data simulation, goodness-of-fit evaluation, regularization parameter tuning, and visualization of results, as well as predictions in new data.

Version: 1.0.0
Imports: circlize (≥ 0.4.14), ComplexHeatmap, glasso (≥ 1.11), glmnet (≥ 4.1.4), mvtnorm (≥ 1.1.3), pbapply (≥ 1.5.0), Rcpp (≥, scatterplot3d (≥ 0.3.41)
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2022-10-10
Author: Yixiao Zeng [aut, cre, cph], Celia Greenwood [ths, aut], Archer Yang [ths, aut]
Maintainer: Yixiao Zeng <yixiao.zeng at mail.mcgill.ca>
BugReports: https://github.com/yixiao-zeng/missoNet/issues
License: GPL-2
URL: https://github.com/yixiao-zeng/missoNet
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: missoNet results


Reference manual: missoNet.pdf
Vignettes: An Introduction to missoNet


Package source: missoNet_1.0.0.tar.gz
Windows binaries: r-devel: missoNet_1.0.0.zip, r-release: missoNet_1.0.0.zip, r-oldrel: missoNet_1.0.0.zip
macOS binaries: r-release (arm64): missoNet_1.0.0.tgz, r-oldrel (arm64): missoNet_1.0.0.tgz, r-release (x86_64): missoNet_1.0.0.tgz, r-oldrel (x86_64): missoNet_1.0.0.tgz


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