Package: missoNet 1.2.0
Yixiao Zeng
missoNet: Missingness in Multi-Task Regression with Network Estimation
Efficient procedures for fitting conditional graphical lasso models that link a set of predictor variables to a set of response variables (or tasks), even 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. Additionally, 'missoNet' estimates the response network structure influenced by conditioning predictor variables using a L1-regularized conditional Gaussian graphical model. Unlike most penalized multi-task regression methods (e.g., MRCE), 'missoNet' is capable 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 to the estimates obtained without missingness.
Authors:
missoNet_1.2.0.tar.gz
missoNet_1.2.0.zip(r-4.5)missoNet_1.2.0.zip(r-4.4)missoNet_1.2.0.zip(r-4.3)
missoNet_1.2.0.tgz(r-4.4-x86_64)missoNet_1.2.0.tgz(r-4.4-arm64)missoNet_1.2.0.tgz(r-4.3-x86_64)missoNet_1.2.0.tgz(r-4.3-arm64)
missoNet_1.2.0.tar.gz(r-4.5-noble)missoNet_1.2.0.tar.gz(r-4.4-noble)
missoNet_1.2.0.tgz(r-4.4-emscripten)missoNet_1.2.0.tgz(r-4.3-emscripten)
missoNet.pdf |missoNet.html✨
missoNet/json (API)
NEWS
| # Install 'missoNet' in R: |
| install.packages('missoNet', repos = c('https://yixiao-zeng.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yixiao-zeng/missonet/issues
conditional-graphical-lassomissing-datamulti-task-regression
Last updated 1 years agofrom:5cbbd9969b. Checks:OK: 7 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 08 2024 |
| R-4.5-win-x86_64 | NOTE | Sep 08 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 08 2024 |
| R-4.4-win-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-x86_64 | OK | Sep 08 2024 |
| R-4.4-mac-aarch64 | OK | Sep 08 2024 |
| R-4.3-win-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-x86_64 | OK | Sep 08 2024 |
| R-4.3-mac-aarch64 | OK | Sep 08 2024 |
Exports:cv.missoNetgenerateDatamissoNet
Dependencies:BiocGenericscirclizeclueclustercodetoolscolorspaceComplexHeatmapcrayondigestdoParallelforeachGetoptLongglassoGlobalOptionsIRangesiteratorsmatrixStatsmvtnormpbapplypngRColorBrewerRcppRcppArmadillorjsonS4Vectorsscatterplot3dshape
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Multi-task regression and conditional network estimation with missing values in the tasks | missoNet-package |
| Cross-validation for missoNet | cv.missoNet |
| Quickly generate synthetic data for simulation studies | generateData |
| Fit a series of missoNet models with user-supplied regularization parameters for the lasso penalties | missoNet |
| Plot the cross-validation errors produced by cv.missoNet | plot.cv.missoNet |
| Make predictions from a cv.missoNet object | predict.cv.missoNet |