euroMix (version 1.1.1)

LRpvalue: Compute the p-value corresponding to a likelihood ratio.

Description

Reads mixture data from files, computes the likelihood ratio for the given hypotheses and finally calculates a p-value corresponding to the likelihood ratio. The p-value is the probability of observing a likelihood ratio at least as large as the one observed, given that the defense hypothesis is true.

Usage

LRpvalue(samplefile, victimfile, suspectfile, freqfile, hp, hd, prD, prC)

Arguments

samplefile

CSV file with sample profile. The file can only contain data for autosomal markers, and apart from that the format is the same as required in LRmix. See the LRmix manual for details. The file name must contain the complete path if the file is not in the current working directory.

victimfile

CSV file with victim profile. Same format as in LRmix. Only autosomal markers.

suspectfile

CSV file with suspect profile. Same format as in LRmix. Only autosomal markers.

freqfile

CSV file with allele frequencies. Same format as in LRmix.

hp

Prosecution hypothesis. A character vector of all contributors under $H_p$, where S denotes suspect, V victim and U unknown. E.g. if the hypothesis is that the sample is a mixture of the suspect, the victim and one unknown, this is specified with the vector c('S','V,'U').

hd

Defense hypothesis. A character vector of all contributors under $H_d$, specified like hp. E.g. if the hypothesis is that the sample is a mixture of the suspect, and two unknowns, this is specified with the vector c('S','U,'U').

prD

Probability of drop-out. A number between 0 and 1.

prC

Probability of drop-in. A number between 0 and 1.

Value

LR

Likelihood ratio

pvalue

P-value corresponding to the likelihood ratio

Details

The function is a wrapper for LRp which again is a wrapper for pvalue.machine. Likelihood ratios are computed with the LR function in forensim. For liberties regarding reading data from files, LRp can be used to compute p-values for already prepared data frames. For liberty also regarding the LR model used, pvalue.machine is the most generic function to compute a p-value.

References

Dorum et al. Exact computation of the distribution of likelihood ratios with forensic applications. FSI: Genetics, 9, 2014, doi: http://dx.doi.org/10.1016/j.fsigen.2013.11.008

See Also

pvalue.machine,LRp

Examples

data(sample);data(suspect);data(victim);data(freqs)
samplefile <- tempfile(); write.table(sample, samplefile, sep=",", row.names=FALSE)
victimfile <- tempfile(); write.table(victim, victimfile, sep=",", row.names=FALSE)
suspectfile <- tempfile(); write.table(suspect, suspectfile, sep=",", row.names=FALSE)
freqfile <- tempfile(); write.table(freqs, freqfile, sep=",", row.names=FALSE)

LRpvalue(samplefile, victimfile, suspectfile, freqfile, hp=c("V","S"), hd=c("V","U"), 
prD=0.47, prC=0.05)
unlink(c(samplefile, victimfile, suspectfile, freqfile))