selection_criteria: Calculate selection criteria.
In cobiclust: Biclustering via Latent Block Model Adapted to Overdispersed Count Data
Description
Usage
Arguments
Value
Description
Calculate selection criteria.
Usage
1
selection_criteria(x, K, G)
Arguments
x
The output of the cobiclust function.
K
The number of groups in rows.
G
The number of groups in columns.
Value
A dataframe with 7 columns.
vICLthe vICL selection criterion.
BICthe BIC selection criterion.
penKGthe value of the BIC penalty.
lbthe value of the lower bound of the log-likelihood.
entZWthe value of the entropy of the latent variables Z and W.
Kthe number of groups in rows.
Gthe number of groups in columns.
cobiclust documentation built on May 1, 2019, 9:14 p.m.
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Description Usage Arguments Value
Description
Calculate selection criteria.
Usage
1 | selection_criteria(x, K, G)
|
Arguments
x |
The output of the cobiclust function. |
K |
The number of groups in rows. |
G |
The number of groups in columns. |
Value
A dataframe with 7 columns.
vICLthe vICL selection criterion.
BICthe BIC selection criterion.
penKGthe value of the BIC penalty.
lbthe value of the lower bound of the log-likelihood.
entZWthe value of the entropy of the latent variables Z and W.
Kthe number of groups in rows.
Gthe number of groups in columns.
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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