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Classification of percentages in seizures of narcotic material
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences. Swedish Police Auhtority, National Forensic Centre (NFC).ORCID iD: 0000-0001-9385-5443
2017 (English)Conference paper, Oral presentation only (Other academic)
Abstract [en]

The percentage of the narcotic substance in a drug seizure may vary a lot depending on when and from whom the seizure was taken. Seizures from a typical consumer would in general show low percentages, while seizures from the early stages of a drug dealing chain would show higher percentages (these will be diluted). Legal fact finders must have an up-to-date picture of what is an expected level of the percentage and what levels are to be treated as unusually low or unusually high. This is important for the determination of the sentences to be given in a drug case.

In this work we treat the probability distribution of the percentage of a narcotic substance in a seizure from year to year as a time series of beta density functions, which are successively updated with the use of point mass posteriors for the shape parameters. The predictive distribution for a new year is a weighted sum of beta distributions for the previous years where the weights are found from forward validation. We show that this method of prediction is more accurate than one that uses a predictive distribution built on a likelihood based on all previous years.

Place, publisher, year, edition, pages
2017.
National Category
Probability Theory and Statistics Law and Society
Identifiers
URN: urn:nbn:se:liu:diva-159536OAI: oai:DiVA.org:liu-159536DiVA, id: diva2:1342029
Conference
10th International Conference on Forensic Inference and Statistics
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-08-12

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Nordgaard, Anders
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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf