reduce_pca: Reducing using the first principal component for...
In cdgreenidge/brcbase:
Description
Usage
Arguments
Value
Description
If mat is a matrix with no columns, the all 0-vector is returned. Be warned that
the first principal component is not unique, as the negative of the returned
value is also a valid first principal component. We use the first principal
component decided upon by stat::princomp.
Usage
1
reduce_pca(mat)
Arguments
mat
The matrix where each column represents a time series with nrow(mat)
values.
Value
A vector with nrow(mat) values
cdgreenidge/brcbase documentation built on May 13, 2019, 2:40 p.m.
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Description Usage Arguments Value
Description
If mat is a matrix with no columns, the all 0-vector is returned. Be warned that the first principal component is not unique, as the negative of the returned value is also a valid first principal component. We use the first principal component decided upon by stat::princomp.
Usage
1 | reduce_pca(mat)
|
Arguments
mat |
The matrix where each column represents a time series with nrow(mat) values. |
Value
A vector with nrow(mat) values
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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