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missoNet
View on CRAN: Click
here
Download and install missoNet package within the R console
Install from CRAN:
install.packages("missoNet")
Install from Github:
library("remotes")
install_github("cran/missoNet")
Install by package version:
library("remotes")
install_version("missoNet", "1.2.0")
Attach the package and use:
library("missoNet")
Maintained by
Yixiao Zeng
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-10
Latest Update: 2023-07-19
Description:
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.
How to cite:
Yixiao Zeng (2022). missoNet: Missingness in Multi-Task Regression with Network Estimation. R package version 1.2.0, https://cran.r-project.org/web/packages/missoNet. Accessed 21 Nov. 2024.
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Other R packages that missoNet depends,
imports, suggests or enhances
Complete documentation for missoNet
Functions, R codes and Examples using
the missoNet R package
Some associated functions: cv.missoNet . generateData . missoNet-package . missoNet . plot.cv.missoNet . predict.cv.missoNet .
Some associated R codes: InitLambda.R . InitParams.R . RcppExports.R . boundaryCheck.R . cv.missoNet.R . generateData.R . getResCov.R . maxproj.cov.R . missoNet-package.R . missoNet.R . parWrapper.R . plot.cv.missoNet.R . plot.heatmap.R . plot.scatter.R . predict.cv.missoNet.R . relax.glasso.R . simfun.R . update.missoNet.R . zzz.R . Full missoNet package functions and examples
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