A probabilistic approach to heroin signatures

Analytical and Bioanalytical Chemistry

Volumn 396, Issue 2, 2010, Pages 765-773

  Hibbert, D Brynn ^a   Blackmore, Danielle ^a   Li, Jianfeng ^a   Ebrahimi, Diako ^a   Collins, Michael ^b   Vujic, Sasha ^b   Gavoyannis, Paul ^b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b NATIONAL MEASUREMENT INSTITUTE   (Australia)

Author keywords

Bayes' theorem; Bayesian classification; Codeine; Diacetyl morphine; Drug identification; Heroin; Heroin analysis; Heroin signature program; Illicit drug analysis; Likelihood; Monoacetyl morphine; Morphine; Probability density function

Indexed keywords

BAYES' THEOREM; BAYESIAN CLASSIFICATION; DIACETYL; DRUG IDENTIFICATION; ILLICIT DRUG;

BAYESIAN NETWORKS; MAXIMUM LIKELIHOOD ESTIMATION; PROBABILITY;

PROBABILITY DENSITY FUNCTION;

DIAMORPHINE;

CONFERENCE PAPER; LIQUID CHROMATOGRAPHY; MEXICO; SOUTH AMERICA; SOUTHEAST ASIA;

ASIA, SOUTHEASTERN; CHROMATOGRAPHY, LIQUID; HEROIN; MEXICO; SOUTH AMERICA;

EID: 76849105376     PISSN: 16182642     EISSN: 16182650     Source Type: Journal    
DOI: 10.1007/s00216-009-3260-4     Document Type: Conference Paper

References (13)

1. Costa AM (2007) World Drug Report. United Nations Office on Drugs and Crime, Vienna, Austria
2. LR Odell J Skopec A McCluskey 2006 A 'cold synthesis' of heroin and implications in heroin signature analysis: Utility of trifluoroacetic/acetic anhydride in the acetylation of morphine Forensic Sci Int 164 221 229 10.1016/j.forsciint.2006.02.009 1:CAS:528:DC%2BD28XhtFKmtrbJ (Pubitemid 44755252)
3. Hast RH (2001) Review of the Drug Enforcement Administration's Heroin Signature and Domestic Monitor Programs. U.S. General Accounting Office, Washington, D.C., p 8
4. Hutchinson A (2002) Drug control: DEA could improve its heroin signature and domestic monitor programs' geographic source data. United States General Accounting Office, Washington, DC, p 37
5. United Nations (1998) Recommended methods for testing opium, morphine and heroin. In: U.N.I.D.C. Programme, (Ed.), United Nations, New York, pp. 11
6. N Nic Daeid RJH Waddell 2005 The analytical and chemometric procedures used to profile illicit drug seizures Talanta 67 280 285 10.1016/j.talanta.2005. 05.018 1:CAS:528:DC%2BD2MXntVygtro%3D (Pubitemid 41101243)
7. IS Lurie PA Hays AE Garcia S Panicker 2004 Use of dynamically coated capillaries for the determination of heroin, basic impurities and adulterants with capillary electrophoresis J chromatogr A 1034 227 235 10.1016/j.chroma. 2004.01.062 1:CAS:528:DC%2BD2cXisVGht74%3D (Pubitemid 38376436)
8. IS Lurie SM Carr 1986 The quantitation of heroin and selected basic impurities via reversed phase HPLC. I. The analysis of unadulterated heroin samples J Liq Chromatogr 9 2485 2509 10.1080/01483918608076880 1:CAS:528:DyaL28XlvVGgsbY%3D
9. IS Lurie 1990 The use of multiple detectors for HPLC forensic drug analysis LC-GC 8 454 466 1:CAS:528:DyaK3cXksFeku70%3D
10. N Armstrong DB Hibbert 2009 An introduction to Bayesian methods for analyzing chemistry data. Part 1: an introduction to Bayesian theory and methods Chemometr Intell Lab Syst 97 194 210 10.1016/j.chemolab.2009.04.001 1:CAS:528:DC%2BD1MXmtlWmtb4%3D
11. DB Hibbert N Armstrong 2009 An introduction to Bayesian methods for analyzing chemistry data. Part II: a review of applications of Bayesian methods in chemistry Chemometr Intell Lab Syst 97 211 220 10.1016/j.chemolab.2009.03.009 1:CAS:528:DC%2BD1MXmtlWmtb8%3D
12. Analytical Methods Committee (2006) Representing data distributions with kernel density estimates, AMC Technical Brief. Royal Society of Chemistry, Cambridge, p 2
13. SJ Sheather MC Jones 1991 A reliable data-based bandwidth selection method for kernel density estimation J R Stat Soc, Ser B 53 683 690