generate_inv_cov: generate_inv_cov
In FrankD/nethet: A bioconductor package for high-dimensional exploration of biological network heterogeneity
Description
Usage
Arguments
Details
Value
Examples
Description
Generate an inverse covariance matrix with a given sparsity and
dimensionality
Usage
1
generate_inv_cov(p = 162, sparsity = 0.7)
Arguments
p
Dimensionality of the matrix.
sparsity
Determined the proportion of non-zero off-diagonal entries.
Details
This function generates an inverse covariance matrix, with at most
(1-sparsity)*p(p-1)
non-zero off-diagonal entries, where the non-zero entries are sampled from a
beta distribution.
Value
A p by p positive definite inverse covariance matrix.
Examples
1
generate_inv_cov(p=162)
FrankD/nethet documentation built on Oct. 5, 2020, 8:22 a.m.
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Description Usage Arguments Details Value Examples
Description
Generate an inverse covariance matrix with a given sparsity and dimensionality
Usage
1 | generate_inv_cov(p = 162, sparsity = 0.7)
|
Arguments
p |
Dimensionality of the matrix. |
sparsity |
Determined the proportion of non-zero off-diagonal entries. |
Details
This function generates an inverse covariance matrix, with at most (1-sparsity)*p(p-1) non-zero off-diagonal entries, where the non-zero entries are sampled from a beta distribution.
Value
A p by p positive definite inverse covariance matrix.
Examples
1 | generate_inv_cov(p=162)
|
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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