rank_reduce: Rank reduding
In proto4426/ValUSunSSN: Val-U-Sun project functions
Description
Usage
Arguments
Details
Value
Examples
Description
rank_reduce() generates a low-rank version version of matrix X by computing
its SVD, and then then reconstructing X by keeping only its ncomp most important
singular values.
Usage
1
rank_reduce(X, ncomp)
Arguments
X
Numeric matrix
ncomp
number of significant components
Details
This function bypasses the (slower) full computation of the SVD by
estimating the singular vectors through diagonalisation of the covariance matrix of X
Value
The corresponding reduced rank version of X
Examples
1
rank_reduce(dataSSN, ncomp = 10)
proto4426/ValUSunSSN documentation built on May 26, 2019, 10:31 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Details Value Examples
Description
rank_reduce() generates a low-rank version version of matrix X by computing
its SVD, and then then reconstructing X by keeping only its ncomp most important
singular values.
Usage
1 | rank_reduce(X, ncomp)
|
Arguments
X |
Numeric matrix |
ncomp |
number of significant components |
Details
This function bypasses the (slower) full computation of the SVD by estimating the singular vectors through diagonalisation of the covariance matrix of X
Value
The corresponding reduced rank version of X
Examples
1 | rank_reduce(dataSSN, ncomp = 10)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.