Nothing
library('stats')
library('likeLTD')
# Case we are going to be looking at.
caseName = 'hammer'
datapath = file.path(system.file("extdata", package="likeLTD"), caseName)
args = list(
databaseFile = NULL,
cspFile = file.path(datapath, 'hammer-CSP.csv'),
refFile = file.path(datapath, 'hammer-reference.csv'),
nUnknowns = 0,
doDropin = TRUE,
ethnic = "NDU1",
adj = 1.0,
fst = 0.02,
relatedness = c(0, 0)/4
)
# Create hypothesis for defence and prosecution.
prosecutionHyp = do.call(prosecution.hypothesis, args)
defenceHyp = do.call(defence.hypothesis, args)
# Create optimisation parameters, with some modification to hypothesis
# arguments. nUnknowns is modified here and now. It does not need to be, but it
# can be. The somethingParams values contain the objective functions and
# optimisation parameters.
prosecutionParams <- optimisation.params(prosecutionHyp, verbose=TRUE,
nUnknowns=1)
defenceParams <- optimisation.params(defenceHyp, verbose=FALSE, nUnknowns=2)
# Now perform actual optimization.
prosecutionResult <- do.call(optim, prosecutionParams)
print(prosecutionResult)
# defenceResult <- do.call(optim, defenceParams)
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