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ipflasso
View on CRAN: Click
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Download and install ipflasso package within the R console
Install from CRAN:
install.packages("ipflasso")
Install from Github:
library("remotes")
install_github("cran/ipflasso")
Install by package version:
library("remotes")
install_version("ipflasso", "1.1")
Attach the package and use:
library("ipflasso")
Maintained by
Anne-Laure Boulesteix
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-11-24
Latest Update: 2019-12-10
Description:
The core of the package is cvr2.ipflasso(), an extension of glmnet to be used when the (large) set of available predictors is partitioned into several modalities which potentially differ with respect to their information content in terms of prediction. For example, in biomedical applications patient outcome such as survival time or response to therapy may have to be predicted based on, say, mRNA data, miRNA data, methylation data, CNV data, clinical data, etc. The clinical predictors are on average often much more important for outcome prediction than the mRNA data. The ipflasso method takes this problem into account by using different penalty parameters for predictors from different modalities. The ratio between the different penalty parameters can be chosen from a set of optional candidates by cross-validation or alternatively generated from the input data.
How to cite:
Anne-Laure Boulesteix (2015). ipflasso: Integrative Lasso with Penalty Factors. R package version 1.1, https://cran.r-project.org/web/packages/ipflasso
Other packages that cited ipflasso R package
View ipflasso citation profile
Other R packages that ipflasso depends,
imports, suggests or enhances
Functions, R codes and Examples using
the ipflasso R package
Some associated functions: cvr.adaptive.ipflasso . cvr.glmnet . cvr.ipflasso . cvr2.ipflasso . ipflasso.predict . my.auc .
Some associated R codes: cvr.adaptive.ipflasso.R . cvr.glmnet.R . my.auc.R . Full ipflasso package functions and examples
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