JavaScript dashboard that can be interrogated on the user’s local machine or
Suggests: faviconPlease, ggplot2, opencpu, tinytest (>= 1.2.3), ttdo
Packaged: 2021-07-23 16:45:49 UTC; jdblischak

Packaged: 2021-08-04 16:52:36 UTC; jdblischak

Packaged: 2021-12-01 04:47:56 UTC; jdblischak

Title: Perform Two-Way Orthogonal Partial Least Squares
Author: Said el Bouhaddani, Jeanine Houwing-Duistermaat, Geurt Jongbloed, Szymon Kielbasa and
Maintainer: Said el Bouhaddani <s.el_bouhaddani@lumc.nl>
Description: Performs the O2PLS data integration method for two datasets yielding joint and data-specific parts for each dataset.
The algorithm automatically switches to a memory-efficient approach to fit O2PLS to high dimensional data.
It provides a rigorous and a faster alternative cross-validation method to select the number of components,
as well as functions to report proportions of explained variation and to construct plots of your results.
Suggests: testthat, knitr, rmarkdown, gplots,
Packaged: 2017-05-08 21:47:30 UTC; selbouhaddani

as well as functions to report proportions of explained variation and to construct plots of the results.
Packaged: 2017-07-08 13:28:18 UTC; selbouhaddani

Packaged: 2017-08-07 22:27:31 UTC; selbouhaddani

Packaged: 2018-01-22 11:40:01 UTC; selbouhaddani

Title: Data Integration with Two-Way Orthogonal Partial Least Squares
Maintainer: Said el Bouhaddani <s.elbouhaddani@umcutrecht.nl>
See the software article by el Bouhaddani et al (2018) <doi:10.1186/s12859-018-2371-3>, and Trygg and Wold (2003) <doi:10.1002/cem.775>.
Imports: ggplot2, parallel, magrittr, tibble
Suggests: testthat, knitr, rmarkdown, gplots

Author: Said el Bouhaddani, Zhujie Gu, Jeanine Houwing-Duistermaat, Geurt Jongbloed, Szymon Kielbasa and
Description: Performs the O2PLS data integration method for two datasets, yielding joint and data-specific parts for each dataset.
See the software article by el Bouhaddani et al (2018) <doi:10.1186/s12859-018-2371-3>,
It also performs Sparse Group (Penalized) O2PLS, see Gu et al (2020) <doi:10.1186/s12859-021-03958-3> and cross-validation for the degree of sparsity.
Imports: graphics, stats, dplyr, ggplot2, parallel, magrittr, tibble,