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milr  

Multiple-Instance Logistic Regression with LASSO Penalty
View on CRAN: Click here


Download and install milr package within the R console
Install from CRAN:
install.packages("milr")

Install from Github:
library("remotes")
install_github("cran/milr")

Install by package version:
library("remotes")
install_version("milr", "0.4.1")



Attach the package and use:
library("milr")
Maintained by
Ping-Yang Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-07-14
Latest Update: 2020-10-31
Description:
The multiple instance data set consists of many independent subjects (called bags) and each subject is composed of several components (called instances). The outcomes of such data set are binary or categorical responses, and, we can only observe the subject-level outcomes. For example, in manufacturing processes, a subject is labeled as "defective" if at least one of its own components is defective, and otherwise, is labeled as "non-defective". The 'milr' package focuses on the predictive model for the multiple instance data set with binary outcomes and performs the maximum likelihood estimation with the Expectation-Maximization algorithm under the framework of logistic regression. Moreover, the LASSO penalty is attached to the likelihood function for simultaneous parameter estimation and variable selection.
How to cite:
Ping-Yang Chen (2016). milr: Multiple-Instance Logistic Regression with LASSO Penalty. R package version 0.4.1, https://cran.r-project.org/web/packages/milr. Accessed 30 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:30), 0.1.0 (2016-07-14 20:15), 0.2.0 (2017-01-10 19:03), 0.3.0 (2017-06-08 18:37), 0.3.1 (2020-10-31 08:30)
Other packages that cited milr R package
View milr citation profile
Other R packages that milr depends, imports, suggests or enhances
Complete documentation for milr
Functions, R codes and Examples using the milr R package
Some associated functions: DGP . fitted.milr . fitted.softmax . logit . milr-package . milr . predict.milr . predict.softmax . softmax . 
Some associated R codes: DGP.R . RcppExports.R . milr-package.R . milr.R . softmax.R .  Full milr package functions and examples
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