calculateEffectiveSamples: Estimated effective samples per feature
In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing
Description
Usage
Arguments
Value
See Also
View source: R/calculateEffectiveSamples.R
Description
Calculates the number of estimated effective samples per feature from the output
of a fitZig run. The estimated effective samples per feature is calculated as the
sum_1^n (n = number of samples) 1-z_i where z_i is the posterior probability a feature
belongs to the technical distribution.
Usage
1
Arguments
obj
The output of fitZig run on a MRexperiment object.
Value
A list of the estimated effective samples per feature.
See Also
metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.
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Description Usage Arguments Value See Also
View source: R/calculateEffectiveSamples.R
Description
Calculates the number of estimated effective samples per feature from the output of a fitZig run. The estimated effective samples per feature is calculated as the sum_1^n (n = number of samples) 1-z_i where z_i is the posterior probability a feature belongs to the technical distribution.
Usage
1 |
Arguments
obj |
The output of fitZig run on a MRexperiment object. |
Value
A list of the estimated effective samples per feature.
See Also
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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