compositions_hard_null: Simulated compositional data with no feature correlations
In george-weingart/banocc: Bayesian ANalysis Of Compositional Covariance
Description
Usage
Format
Value
Description
These are the normalized samples corresponding to counts_hard_null.
They should have a very different correlation structure from the counts.
In particular, there should be one strong, positive association which
is not present in the count correlation structure.
Usage
1
Format
A data frame with 1000 rows (compositional samples) and 9
variables (the features)
Value
A data frame with 1000 compositional samples from 9 features,
generated by dividing each row of counts_hard_null by its sum.
george-weingart/banocc documentation built on May 17, 2019, 1:12 a.m.
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Description Usage Format Value
Description
These are the normalized samples corresponding to counts_hard_null.
They should have a very different correlation structure from the counts.
In particular, there should be one strong, positive association which
is not present in the count correlation structure.
Usage
1 |
Format
A data frame with 1000 rows (compositional samples) and 9 variables (the features)
Value
A data frame with 1000 compositional samples from 9 features,
generated by dividing each row of counts_hard_null by its sum.
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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