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R functions
Philipp-Neubauer edited this page Jan 8, 2013
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This is a short overview of R functions - this will likely develop into a proper R package once Julia is more stable (i.e., V>1.0).
- commented example of the package
DPM_call(datas=NULL,baseline=NULL,labels=NULL,learn=FALSE,iters=1000,thin=10,np=1, typeof='N',path.to.julia=getwd(),call_DPM_path=getwd())
- implemented in (Julia_call_function.R), calls MCMC for Dirichlet process models
- set learn=T for model with baseline
- set appropriate path_to_julia if julia files are not in the working directory
- typeof: 'N' for normal inference (default, and only one available for now), 'MN' for multinomial (allel frequency data) and 'Both' for a combined analysis
MM_call(datas=NULL,baseline=NULL,labels=NULL,conditional=FALSE,iters=1000,thin=10,np=1, typeof='N',path.to.julia=getwd(),call_DPM_path=getwd())
- implemented in (Julia_call_function.R), calls MCMC for finite mixture models
- set conditional=T for conditional mixture analysis (e.g., Munch & Clarke 2008), set to False for unconditional (Smith & Campana 2010, Pella & Masusda references).
- set appropriate path_to_julia if julia files are not in the working directory
- typeof: 'N' for normal inference (default, and only one available for now), 'MN' for multinomial (allel frequency data) and 'Both' for a combined analysis
elink.call(class.ids,path.to.julia=getwd(),elink_path=getwd())
- implements exact linkage in Julia
- set appropriate path_to_julia if julia files are not in the working directory
- class.ids are the individual class.ids as output from the MCMC sampler. Would work with any other sampler as well (e.g., finite mixture models)
as.phylogg(Z,N,tip.label=as.character(1:N))
- converts output from exact linkage algorithm (Z) to ape 'phylo' format for tree visualization.
- N is the number of tips
- tip.label are individual sample labels