@article{ref1,
title="Statistical methods in criminal inference using DNA fingerprints",
journal="Computational statistics and data analysis",
year="1999",
author="Lee, Hye-Seung and Lee, Jae Won",
volume="32",
number="1",
pages="47-67",
abstract="Each of us is genetically unique with the exception of an identical twin. DNA fingerprinting is the evaluation of genetic variation using DNA (Deoxyribonucleic acid). Because a DNA fragment has a large number of distinct alleles and is not degraded rapidly following environmental exposure, it is highly useful in criminal inference such as rape and murder. However, inference using DNA fingerprint data has been conducted with substantial controversies which are mostly due to the probabilistic interpretation of DNA profiles regarding measurement error and the assumption of independent allele. Although some methods for summarizing the data based on measurement error were suggested, they all assumed the independence of alleles both within and between loci. In this article, we compare by simulation and a numerical example three well-known methods for summarizing the data in various types of reference population.<p />",
language="",
issn="0167-9473",
doi="10.1016/S0167-9473(99)00022-5",
url="http://dx.doi.org/10.1016/S0167-9473(99)00022-5"
}