low_dim_vis: Low dimensional data representation. Compute reduced...
In nlhuong/buds: Bayesian Unidimensional Scaling (BUDS)
Description
Usage
Arguments
Value
Description
Low dimensional data representation.
Compute reduced representations of the data.
A wrapper for cmdscale and Rtsne::Rtsne()
Usage
1
low_dim_vis(D, method = "PCoA", dims = 2, ...)
Arguments
D
A pairwise dissimilarity matrix.
method
[Optional] A dimensionality reduction
method either "PCoA" or "tSNE". Default is "PCoA".
dims
[Optional] An integer for the number of dimensions
for to keep. Default is 2.
...
other parameters for Rtsne::Rtsne() function
Value
A data frame with the low-dimensional
represenation.
nlhuong/buds documentation built on May 17, 2019, 3:13 a.m.
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Description Usage Arguments Value
Description
Low dimensional data representation. Compute reduced representations of the data. A wrapper for cmdscale and Rtsne::Rtsne()
Usage
1 | low_dim_vis(D, method = "PCoA", dims = 2, ...)
|
Arguments
D |
A pairwise dissimilarity matrix. |
method |
[Optional] A dimensionality reduction method either "PCoA" or "tSNE". Default is "PCoA". |
dims |
[Optional] An integer for the number of dimensions for to keep. Default is 2. |
... |
other parameters for Rtsne::Rtsne() function |
Value
A data frame with the low-dimensional represenation.
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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