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TULIP
View on CRAN: Click
here
Download and install TULIP package within the R console
Install from CRAN:
install.packages("TULIP")
Install from Github:
library("remotes")
install_github("cran/TULIP") Install by package version:
library("remotes")
install_version("TULIP", "1.0.2") Attach the package and use:
library("TULIP")
Maintained by
Yuqing Pan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-04-09
Latest Update: 2021-01-04
Description:
Integrates several popular high-dimensional methods based on Linear Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification as mentioned in Yuqing Pan, Qing Mai and Xin Zhang (2019) <doi:10.48550/arXiv.1904.03469>. Functions are included for covariate adjustment, model fitting, cross validation and prediction.
How to cite:
Yuqing Pan (2019). TULIP: A Toolbox for Linear Discriminant Analysis with Penalties. R package version 1.0.2, https://cran.r-project.org/web/packages/TULIP. Accessed 06 Mar. 2026.
Other packages that cited TULIP R package
View TULIP citation profile
Other R packages that TULIP depends,
imports, suggests or enhances
Complete documentation for TULIP
Functions, R codes and Examples using
the TULIP R package
Some associated functions: GDS1615 . ROAD . SOS . SeSDA . adjten . adjvec . catch . catch_matrix . csa . cv.SeSDA . cv.dsda . cv.msda . cvcatch . dsda.all . dsda . getnorm . msda . predict.SeSDA . predict.catch . predict.dsda . predict.msda . sim.bi.vector . sim.tensor.cov .
Some associated R codes: Mmsda.R . Omsda.R . ROAD.R . SOS.R . SeSDA.R . adjust_predict.R . adjusttensor.R . adjvec.R . catch.R . catch_matrix.R . cv.Mmsda.R . cv.Omsda.R . cv.SeSDA.R . cv.catch.R . cv.dsda.R . cv.folds.R . cv.msda.R . dsda.R . dsda.all.R . dsda_noadj.R . getnorm.R . getnorm.naive.R . getnorm.pool.R . msda.R . msda_noadj.R . predict.SeSDA.R . predict.dsda.R . predict.msda.R . predict.msda.modified.R . predict.msda.original.R . sim.bi.vector.R . sim.tensor.cov.R . tensor_main.R . tensor_predict.R . tensor_utility.R . truncate.R . utilities.R . Full TULIP package functions and examples
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