preprocess: Preprocessing
In rudazhang/plmr: Probabilistic Learning on Manifolds in R
Description
Usage
Arguments
Details
Value
View source: R/DMapProjection.R
Description
Preprocessing
Usage
1
preprocess(X0, scale = FALSE)
Arguments
X0
The original sample matrix, m-by-n; can be a data.frame.
scale
A logical for whether the variables should be scaled.
Details
All PC coordinates are currently assumed to be non-degenerate.
Further generalization is needed.
Value
A list: pc, affine transformation to normalized principal component (PC) coordinates;
H0, normalized sample matrix (zero-mean, unit-variance), m-by-n;
rudazhang/plmr documentation built on Aug. 30, 2021, 5:43 p.m.
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Description Usage Arguments Details Value
View source: R/DMapProjection.R
Description
Preprocessing
Usage
1 | preprocess(X0, scale = FALSE)
|
Arguments
X0 |
The original sample matrix, m-by-n; can be a data.frame. |
scale |
A logical for whether the variables should be scaled. |
Details
All PC coordinates are currently assumed to be non-degenerate. Further generalization is needed.
Value
A list: pc, affine transformation to normalized principal component (PC) coordinates; H0, normalized sample matrix (zero-mean, unit-variance), m-by-n;
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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