# two.level.density.LR: Likelihood ratio calculation - kernel density In comparison: Multivariate likelihood ratio calculation and evaluation

## 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

 `1` ```two.level.density.LR(control, recovered, background) ```

## Arguments

 `control` a `compitem` object with the control item information `recovered` a `compitem` object with the recovered item information `background` a `compcovar` object with the populational information

## Details

Does the likelihood ratio calculations for a two-level model without assuming that the between items distribution is uni/multivariate normal.

## Value

Returns an estimate of the likelihood ratio

## Note

Do not even think about using this function without the proper `compcovar` and `compitem` objects - it will not work.

## References

Aitken, C.G.G. & Lucy, D. (2004) Evaluation of trace evidence in the form of multivariate data. Applied Statistics: 53(1); 109-122.

`compcovar`
`compitem`
`two.level.comparison.items`
`two.level.components`
`two.level.normal.LR`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33``` ```# load this library library(comparison) # load Greg Zadora's glass data data(glass) # make it into a data frame dat <- as.data.frame(glass) # calculate a compcovar object based upon dat # using K, Ca and Fe - warning - could take time # on slower machines Z <- two.level.components(dat, c(7,8,9), 1) # calculate a compitem object representing the control item control <- two.level.comparison.items(dat[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(dat[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(dat[19:24,], c(7,8,9)) # calculate the likelihood ratio for a known # same source comparison - should be 20.59322 lr.1 <- two.level.density.LR(control, recovered.1, Z) # calculate the likelihood ratio for a known # different source comparison - should be 0.02901532 lr.2 <- two.level.density.LR(control, recovered.2, Z) ```

comparison documentation built on May 29, 2017, 9:08 a.m.