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BoostMLR
View on CRAN: Click
here
Download and install BoostMLR package within the R console
Install from CRAN:
install.packages("BoostMLR")
Install from Github:
library("remotes")
install_github("cran/BoostMLR") Install by package version:
library("remotes")
install_version("BoostMLR", "1.0.3") Attach the package and use:
library("BoostMLR")
Maintained by
Amol Pande
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-14
Latest Update: 2021-02-25
Description:
Jointly models the multivariate longitudinal responses and multiple covariates and time using gradient boosting approach.
How to cite:
Amol Pande (2020). BoostMLR: Boosting for Multivariate Longitudinal Responses. R package version 1.0.3, https://cran.r-project.org/web/packages/BoostMLR. Accessed 07 Mar. 2026.
Other packages that cited BoostMLR R package
View BoostMLR citation profile
Other R packages that BoostMLR depends,
imports, suggests or enhances
Complete documentation for BoostMLR
Functions, R codes and Examples using
the BoostMLR R package
Some associated functions: BoostMLR-package . BoostMLR.news . BoostMLR . Laboratory_Data . partial.BoostMLR . plotBoostMLR . plotVIMP . predictBoostMLR . simLong . updateBoostMLR . vimp.BoostMLR .
Some associated R codes: BoostMLR.R . BoostMLR.news.R . RcppExports.R . partial.BoostMLR.R . plot.Variable_Select.R . plotBoostMLR.R . plotVIMP.R . predictBoostMLR.R . simLong.R . updateBoostMLR.R . utilities.R . vimp.BoostMLR.R . zzz.R . Full BoostMLR package functions and examples
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