input: Load location data

Description Usage Arguments Value Author(s) Examples

View source: R/bpec.R

Description

Shows all input files and settings used in a BPEC run.

Usage

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input(bpecout)

## S3 method for class 'bpec'
input(bpecout)

Arguments

bpecout

R object from bpec.mcmc run

Value

seqCountOrig

The number of input sequences.

seqLengthOrig

The length of the input sequences.

iter

The number of MCMC iterations.

ds

The parsimony relaxation parameter.

coordsLocs

The input coordinate and observation file.

coordsDims

The input dimension (2 for purely geographical data).

locNo

The number of distinct sampling locations.

locData

The list of coordinates of each observation.

Author(s)

Ioanna Manolopoulou & Axel Hille

Examples

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## if you want to load the `mini' example Brown Frog dataset
data(MacrocnemisRawSeqs)
data(MacrocnemisCoordsLocsMini)
rawSeqs <- MacrocnemisRawSeqs
coordsLocs <- MacrocnemisCoordsLocsMini

dims <- 3 #this is 2 if you only have geographical longitude/latitude. 
#(add 1 for each environmental or phenotypic covariate)
maxMig <- 2 #you will need a higher maximum number of migrations, suggest 7
ds <- 0 #start with ds=0 and increase to 1 and then to 2
iter <- 1000 #you will need far more iterations for convergence, start with 100,000
postSamples <- 100 #you will need at least 100 saved posterior samples

#run the Markov chain Monte Carlo sampler
bpecout <- bpec.mcmc(rawSeqs,coordsLocs,maxMig,iter,ds,postSamples,dims)
input(bpecout)

BPEC documentation built on March 2, 2020, 1:07 a.m.