getMatCorSVD: Perform singular Value Decomposition on the correlation...
In vincela/VarExp: Computes phenotypic variance explained by a set of genetic and/or interaction effects
Description
Usage
Arguments
Value
Examples
View source: R/correlationMatrix.R
Description
Perform singular Value Decomposition on the correlation matrix
Usage
1
getMatCorSVD(cormat, k = qr(cormat)$rank)
Arguments
cormat
is the correlation matrix
k
is the number of eigen vectors to keep. Default is the correlation matrix rank.
Value
A list with :
- eigval
A vector of the top k eigenvalues
- eigvev
A matrix of the top k eigen vectors
Examples
1
2
3
4
a = matrix(runif(10*10,1,5),nrow=10)
matcor = cor(a)
getMatCorSVD(matcor)
getMatCorSVD(matcor, k = 4)
vincela/VarExp documentation built on May 29, 2019, 12:42 p.m.
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Description Usage Arguments Value Examples
View source: R/correlationMatrix.R
Description
Perform singular Value Decomposition on the correlation matrix
Usage
1 | getMatCorSVD(cormat, k = qr(cormat)$rank)
|
Arguments
cormat |
is the correlation matrix |
k |
is the number of eigen vectors to keep. Default is the correlation matrix rank. |
Value
A list with :
- eigval
A vector of the top
keigenvalues- eigvev
A matrix of the top
keigen vectors
Examples
1 2 3 4 | a = matrix(runif(10*10,1,5),nrow=10)
matcor = cor(a)
getMatCorSVD(matcor)
getMatCorSVD(matcor, k = 4)
|
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.
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