addRandomSolutions.BigBang: Adds random pre-existed solutions

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Adds random pre-existed solutions. The purpose is to “simulate” new solutions in order to see gene stability and gene frequency. The results are biased but can be used to estimate the how many more solutions are needed to stabilize certain number of genes.

Usage

## S3 method for class 'BigBang'
addRandomSolutions(no, n=length(no$bestChromosomes), ...)

Arguments

n	number of solutions to add

Value

Returns nothing. However, the original BigBang object has been modified adding the random solutions.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see BigBang.

Examples

   #bb is a BigBang object
   ## Not run: 
   bb
   plot(bb)
   addRandomSolutions(bb, 1000)
   plot(bb) # accumulated solutions
   
## End(Not run)
 

galgo documentation built on May 2, 2019, 4:20 a.m.