get.mca: Calculates the matrices needed for PMCA using two coupled...
In robyn-ball/PMCA: Permutation-based Maximum Covariance Analysis
Description
Usage
Arguments
Value
Examples
Description
Calculates the matrices needed for PMCA using two coupled datasets
Usage
1
get.mca(X, Y)
Arguments
X
a matrix (p x n) where the columns represent the coupled data (i.e., sample)
Y
a matrix (q x n) where the columns represent the coupled data (i.e., sample)
Value
a list that contains the components of the singular value decomposition
of the covariance matrix of X and Y (u, sigma, v),
the principle components (Px) of the covariance matrix related to X, and
the amplitudes of the co-varying patterns related to X and Y (Zx and Zy),
Examples
1
see README
robyn-ball/PMCA documentation built on Dec. 31, 2020, 3:10 a.m.
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Description Usage Arguments Value Examples
Description
Calculates the matrices needed for PMCA using two coupled datasets
Usage
1 | get.mca(X, Y)
|
Arguments
X |
a matrix (p x n) where the columns represent the coupled data (i.e., sample) |
Y |
a matrix (q x n) where the columns represent the coupled data (i.e., sample) |
Value
a list that contains the components of the singular value decomposition of the covariance matrix of X and Y (u, sigma, v), the principle components (Px) of the covariance matrix related to X, and the amplitudes of the co-varying patterns related to X and Y (Zx and Zy),
Examples
1 | see README
|
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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