R/comparison-package.R

In jmcurran/comparison: Multivariate Likelihood Ratio Calculation and Evaluation

#' comparison: A package for computing likelihood ratios for univariate and
#' multivariate evidence.
#'
#' This package is for computing the *weight of the evidence*, i.e. the
#' *likelihood ratio (LR)* for trace evidence which has been quantified with
#' some instrument. For example a forensic scientist might be have determined
#' the refractive indices of fragments of glass taken from a crime scene and
#' fragments of glass recovered from the clothing of the suspected breaker. This
#' package evaluates the probability (density) of the evidence, \eqn{E}, (the RI
#' values from the two samples) under the hypothesis \eqn{H_p}{Hp} that they
#' originated from the same source, and alternatively under the hypothesis
#' \eqn{H_d}{Hd} that they originated from another source. The LR is the ratio of
#' these two quantities, i.e. \deqn{LR = \frac{p(E|H_p)}{p(E|H_d)}}{LR = p(E|Hp) / pr(E|Hd)}.
#' A \eqn{LR} which is greater than one indicates that the evidence supports \eqn{H_p}{Hp}, and a 
#' \eqn{LR} which is less than one indicates that the evidence supports \eqn{H_d}{Hd}.
#'
#' The computation can use either univariate or multivariate observations of a
#' physical object. For example trace element measurements, and a similar set of
#' uni/multivariate observations from another object, and calculates a
#' likelihood ratio for the propositions that the first item came from the same
#' source as the second given some population data.
#'
#'
#' ### Acknowledgements
#'
#' In a package of functions such as these which have undergone a long
#' development over a number of years, it is inevitable that a number of people,
#' besides those directly cited, have helped to correct and add to the code.
#' These people are (in alphabetical order): Ivo Alberink (NFI), Anabel Bolck
#' (NFI), Sonja Menges (BKA), Geoff Morrison (Aston), Tereza Neocleous
#' (Glasgow), Anders Nordgaard (SKL), Brad Patterson (George Mason), Phil Rose
#' (ANU), Agnieszka Rzepecka (Jagiellonian), Marjan Sjerps (NFI) and Hanjing
#' Zhang (Edinburgh).
#'
#'
#' @references Aitken, C.G.G. & Lucy, D. (2004) Evaluation of trace evidence in
#'   the form of multivariate data. Applied Statistics: 53(1):109-122.
#'
#' @keywords package multivariate
#' 
#' @docType package
#' @name comparison
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