Functions for dimension reduction through the seeded canonical correlation analysis are provided. A classical canonical correlation analysis (CCA) is one of useful statistical methods in multivariate data analysis, but it is limited in use due to the matrix inversion for large p small n data. To overcome this, a seeded CCA has been proposed in Im, Gang and Yoo (2015)
|Author||Jae Keun Yoo, Bo-Young Kim|
|Date of publication||2017-08-30 15:19:27 UTC|
|Maintainer||Jae Keun Yoo <[email protected]>|
|License||GPL (>= 2.0)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.