Last data update: 2014.03.03
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R: likeLTD::locus.likes.peaks
locus.likes.peaks | R Documentation |
likeLTD::locus.likes.peaks
Description
Vector with individual locus likelihoods for peak height data.
Usage
locus.likes.peaks(hypothesis,results,...)
Arguments
hypothesis |
The hypothesis generated by either prosecution.hypothesis.peaks
or defence.hypothesis.peaks .
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results |
Either prosecution or defence results from evaluate.peaks
e.g. results$Pros or results$Def .
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... |
Any extra parameter that was passed to evaluate.peaks .
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Details
Convert the overall likelihood returned by evaluate.peaks into locus specific likelihoods.
Value
Vector.
See Also
evaluate.peaks
Examples
## Not run:
# datapath to example files
datapath = file.path(system.file("extdata", package="likeLTD"),"laboratory")
# File paths and case name for allele report
admin = pack.admin.input.peaks(
peaksFile = file.path(datapath, 'laboratory-CSP.csv'),
refFile = file.path(datapath, 'laboratory-reference.csv'),
caseName = "Laboratory",
detectionThresh = 20
)
# Enter arguments
args = list(
nUnknowns = 1
)
# Create hypotheses
hypP = do.call(prosecution.hypothesis.peaks, append(admin,args))
hypD = do.call(defence.hypothesis.peaks, append(admin,args))
# Get parameters for optimisation
paramsP = optimisation.params.peaks(hypP)
paramsD = optimisation.params.peaks(hypD)
# reduce number of iterations for demonstration purposes
paramsP$control$itermax=25
paramsD$control$itermax=25
# Run optimisation
# n.steps and converge set for demonstration purposes
results = evaluate.peaks(paramsP, paramsD, n.steps=1,
converge=FALSE)
# get locus likelihoods under prosecution
locus.likes.peaks(hypP,results$Pros)
# get locus LRs
locus.likes.peaks(hypP,results$Pros)/locus.likes.peaks(hypD,results$Def)
## End(Not run)
Results
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