Object-oriented Bayesian networks for paternity cases with allelic dependencies.
暂无分享,去创建一个
[1] C. Brenner,et al. The Avuncular Index and the Incest Index , 1988 .
[2] William G. Hill,et al. The Evaluation of Forensic DNA Evidence. By Committee on DNA Forensic Science: an Update, National Research Council. National Academy Press, 1996. 254 pages. Price £30.95, hard cover. ISBN 0 309 05395 1. , 1997 .
[3] J. Buckleton,et al. Forensic DNA Evidence Interpretation , 2004 .
[4] Avi Pfeffer,et al. Object-Oriented Bayesian Networks , 1997, UAI.
[5] Dw Van Boxel,et al. Probabilistic Expert Systems for Forensic Inference from Genetic Markers , 2002 .
[6] Jonathan Whitaker,et al. Interpreting small quantities of DNA: the hierarchy of propositions and the use of Bayesian networks. , 2002, Journal of forensic sciences.
[7] James M Curran,et al. What is the magnitude of the subpopulation effect? , 2003, Forensic science international.
[8] D. Balding,et al. Population genetics of STR loci in Caucasians , 2006, International Journal of Legal Medicine.
[9] J. Curran,et al. The appropriate use of subpopulation corrections for differences in endogamous communities. , 2007, Forensic science international.
[10] Norman Fenton,et al. The "Jury Observation Fallacy" and the use of Bayesian Networks to present Probabilistic Legal Arguments , 2007 .
[11] James M Curran,et al. How reliable is the sub-population model in DNA testimony? , 2006, Forensic science international.
[12] Michael I. Jordan,et al. Probabilistic Networks and Expert Systems , 1999 .
[13] Anthropologische Gesellschaft in Wien. Mitteilungen der Anthropologischen Gesellschaft in Wien , 1871 .
[14] Colin Aitken,et al. Bayesian Networks and Probabilistic Inference in Forensic Science , 2006 .
[15] Kevin B. Korb,et al. Bayesian Artificial Intelligence , 2004, Computer science and data analysis series.
[16] F Taroni,et al. A general approach to Bayesian networks for the interpretation of evidence. , 2004, Forensic science international.
[17] J M Curran,et al. Interpreting DNA mixtures in structured populations. , 1999, Journal of forensic sciences.
[18] Alex Biedermann,et al. Two Items of Evidence, No Putative Source: An Inference Problem in Forensic Intelligence , 2006, Journal of forensic sciences.
[19] J Mortera,et al. Object-oriented Bayesian networks for complex forensic DNA profiling problems. , 2007, Forensic science international.
[20] Peter Gill,et al. A comparison of adjustment methods to test the robustness of an STR DNA database comprised of 24 European populations. , 2003, Forensic science international.
[21] B S Weir,et al. The effects of inbreeding on forensic calculations. , 1994, Annual review of genetics.
[22] Paolo Garbolino,et al. A graphical model for the evaluation of cross-transfer evidence in DNA profiles. , 2003, Theoretical population biology.
[23] Kathryn B. Laskey,et al. Network Fragments: Representing Knowledge for Constructing Probabilistic Models , 1997, UAI.
[24] F Taroni,et al. The evaluation of evidence in the forensic investigation of fire incidents. Part II. Practical examples of the use of Bayesian networks. , 2005, Forensic science international.
[25] Fabio Corradi,et al. Forensic identification of relatives of individuals included in a database of DNA profiles , 2006 .
[26] Julia Mortera,et al. Analysis of DNA mixtures using Bayesian networks , 2003 .
[27] F Taroni,et al. The evaluation of evidence in the forensic investigation of fire incidents (Part I): an approach using Bayesian networks. , 2005, Forensic science international.
[28] D J Balding,et al. DNA profile match probability calculation: how to allow for population stratification, relatedness, database selection and single bands. , 1994, Forensic science international.
[29] Robert G Cowell. FINEX: a Probabilistic Expert System for forensic identification. , 2003, Forensic science international.
[30] A. Philip Dawid,et al. An object-oriented Bayesian network for estimating mutation rates , 2003, AISTATS.
[31] I. Evett,et al. Interpreting DNA Evidence: Statistical Genetics for Forensic Scientists , 1998 .
[32] Peter Green,et al. Highly Structured Stochastic Systems , 2003 .