two.level.density.LR {comparison} | R Documentation |
Calculate the likelihood ratio using multivariate KDEs
Description
Takes a compitem
object which represents some control item, and a
compitem
object which represents a recovered item, then uses information
from a compcovar
object, which represents the
information from the population, to calculate a likelihood ratio as a measure
of the evidence given by the observations for the same/different source
propositions.
Usage
two.level.density.LR(control, recovered, background)
Arguments
control |
a |
recovered |
a |
background |
a |
Value
an estimate of the likelihood ratio
References
Aitken, C.G.G. & Lucy, D. (2004) Evaluation of trace evidence in the form of multivariate data. Applied Statistics: 53(1); 109-122.
Examples
library(comparison)
# load Greg Zadora's glass data
data(glass)
# calculate a compcovar object based upon glass
# using K, Ca and Fe - warning - could take time
# on slower machines
Z = two.level.components(glass, c(7,8,9), 1)
# calculate a compitem object representing the control item
control = two.level.comparison.items(glass[1:6,], c(7,8,9))
# calculate a compitem object representing the recovered item
# known to be from the same item (item 1)
recovered.1 = two.level.comparison.items(glass[7:12,], c(7,8,9))
# calculate a compitem object representing the recovered item
# known to be from a different item (item 2)
recovered.2 = two.level.comparison.items(glass[19:24,], c(7,8,9))
# calculate the likelihood ratio for a known
# same source comparison - should be 20.59322
# 2020-08-01 Both this version and the previous version return 20.58967
lr.1 = two.level.density.LR(control, recovered.1, Z)
lr.1
# calculate the likelihood ratio for a known
# different source comparison - should be 0.02901532
# 2020-08-01 Both this version and the previous version return 0.01161392
lr.2 = two.level.density.LR(control, recovered.2, Z)
lr.2
[Package comparison version 1.0.8 Index]