BIC_criterion_FLASH: Compute criterion FLASH
In QuantumClone: Clustering Mutations using High Throughput Sequencing (HTS) Data
Description
Computes BIC from a list of outputs of EM algorithm, then returns the position with minimal BIC
Usage
1
BIC_criterion_FLASH(Obj, Mut_num, k, model.selection, s)
Arguments
Obj
Numeric vector with objective function values
Mut_num
Number of mutations to cluster
k
the number of clusters (in the same order as Obj)
model.selection
The function to minimize for the model selection: can be "AIC", "BIC", or numeric. In numeric, the function
s
Number of samples
QuantumClone documentation built on May 2, 2019, 3:03 a.m.
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Description
Computes BIC from a list of outputs of EM algorithm, then returns the position with minimal BIC
Usage
1 | BIC_criterion_FLASH(Obj, Mut_num, k, model.selection, s)
|
Arguments
Obj |
Numeric vector with objective function values |
Mut_num |
Number of mutations to cluster |
k |
the number of clusters (in the same order as Obj) |
model.selection |
The function to minimize for the model selection: can be "AIC", "BIC", or numeric. In numeric, the function |
s |
Number of samples |
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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