sparseMarkov: Generate a sparse Markov matrix for momentum method to...
In wjawaid/bglab: Berthold Gottgens lab scRNA seq
Description
Usage
Arguments
Details
Value
Author(s)
Description
Generate a sparse Markov matrix for momentum method to generate training data
Usage
1
sparseMarkov(x, nn = ceiling(rowSums(x)), n = ncol(x) - 1)
Arguments
x
Square matrix representing proximity. Try using Gaussian kernel from
maps.
nn
Default ceiling(rowSums(x)). Number of nearest neighbours. The default tries
to ensure that highly connected nodes remain highly connected.
n
Number of cells with equal binding threshold.
Details
Generate a sparse Markov matrix for momentum method to generate training data
Value
Returns normalised transition matrix.
Author(s)
Wajid Jawaid
wjawaid/bglab documentation built on May 4, 2019, 6:33 a.m.
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Description Usage Arguments Details Value Author(s)
Description
Generate a sparse Markov matrix for momentum method to generate training data
Usage
1 | sparseMarkov(x, nn = ceiling(rowSums(x)), n = ncol(x) - 1)
|
Arguments
x |
Square matrix representing proximity. Try using Gaussian kernel from maps. |
nn |
Default ceiling(rowSums(x)). Number of nearest neighbours. The default tries to ensure that highly connected nodes remain highly connected. |
n |
Number of cells with equal binding threshold. |
Details
Generate a sparse Markov matrix for momentum method to generate training data
Value
Returns normalised transition matrix.
Author(s)
Wajid Jawaid
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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