{"id":{"repo_id":"auckland-ms","oai_identifier":"oai:researchspace.auckland.ac.nz:2292/47578"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-ms/oai:researchspace.auckland.ac.nz:2292/47578","repository":{"repo_id":"auckland-ms","name":"University of Auckland","base_url":"https://researchspace.auckland.ac.nz/server/oai/request"},"display":{"title":"Interpreting Forensic Trace Evidence using Multi-Elemental and Spectroscopic Data","abstract":"Over the years, statistics has become a crucial part of forensic science. Forensic scientists are often invited to courts to present expert evidence. They have a duty to perform precise and accurate evidence analysis. Accessibility to the techniques like LIBS, LA-ICP-MS and Raman Microscopy that generate multivariate spectroscopic data, has necessitated the need for advanced statistical methods for evidence analysis. The first aim of this thesis is to ascertain reliability and repeatability of evidential data generated using LIBS. The second objective is to propose statistical methods to perform accurate evaluation of trace evidence (comparisons between evidence recovered from suspects’ clothing and from crime scenes; trace evidence such as glass, tapes, fibre and inks) using spectroscopic data.","abstract_html":"Over the years, statistics has become a crucial part of forensic science. Forensic scientists are often invited to courts to present expert evidence. They have a duty to perform precise and accurate evidence analysis. Accessibility to the techniques like LIBS, LA-ICP-MS and Raman Microscopy that generate multivariate spectroscopic data, has necessitated the need for advanced statistical methods for evidence analysis. The first aim of this thesis is to ascertain reliability and repeatability of evidential data generated using LIBS. The second objective is to propose statistical methods to perform accurate evaluation of trace evidence (comparisons between evidence recovered from suspects’ clothing and from crime scenes; trace evidence such as glass, tapes, fibre and inks) using spectroscopic data.","abstract_has_math":false,"creators":["Gupta, Anjali"],"institution":"ResearchSpace@Auckland","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":[],"advisors":["Curran, JM","Triggs, CM"],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019","date_published":"2019","updated_at":"2026-07-24T01:06:48Z","subjects":[],"languages":[],"rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher."],"rights_urls":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2292/47578","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Curran, JM","Triggs, CM"]},{"key":"dc:creator","label":"Author","values":["Gupta, Anjali"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-08-28T02:15:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2019"]},{"key":"dc:publisher","label":"Institution","values":["ResearchSpace@Auckland"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["UoA99265198514102091"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Statistics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["PhD"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Auckland"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2292/47578"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Over the years, statistics has become a crucial part of forensic science. Forensic scientists are often invited to courts to present expert evidence. They have a duty to perform precise and accurate evidence analysis. Accessibility to the techniques like LIBS, LA-ICP-MS and Raman Microscopy that generate multivariate spectroscopic data, has necessitated the need for advanced statistical methods for evidence analysis. The first aim of this thesis is to ascertain reliability and repeatability of evidential data generated using LIBS. The second objective is to propose statistical methods to perform accurate evaluation of trace evidence (comparisons between evidence recovered from suspects’ clothing and from crime scenes; trace evidence such as glass, tapes, fibre and inks) using spectroscopic data."]},{"key":"dc:title","label":"Title","values":["Interpreting Forensic Trace Evidence using Multi-Elemental and Spectroscopic Data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Curran, JM","Triggs, CM"],"dc:creator":["Gupta, Anjali"],"dc:date.accessioned":["2019-08-28T02:15:30Z"],"dc:date.issued":["2019"],"dc:description.abstract":["Over the years, statistics has become a crucial part of forensic science. Forensic scientists are often invited to courts to present expert evidence. They have a duty to perform precise and accurate evidence analysis. Accessibility to the techniques like LIBS, LA-ICP-MS and Raman Microscopy that generate multivariate spectroscopic data, has necessitated the need for advanced statistical methods for evidence analysis. The first aim of this thesis is to ascertain reliability and repeatability of evidential data generated using LIBS. The second objective is to propose statistical methods to perform accurate evaluation of trace evidence (comparisons between evidence recovered from suspects’ clothing and from crime scenes; trace evidence such as glass, tapes, fibre and inks) using spectroscopic data."],"dc:identifier.uri":["https://hdl.handle.net/2292/47578"],"dc:publisher":["ResearchSpace@Auckland"],"dc:relation.isreferencedby":["UoA99265198514102091"],"dc:rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher."],"dc:rights.uri":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"dc:title":["Interpreting Forensic Trace Evidence using Multi-Elemental and Spectroscopic Data"],"dc:type":["Thesis"],"thesis:degree_discipline":["Statistics"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["PhD"],"thesis:institution_name":["The University of Auckland"]},"updated_at":"2026-07-24T01:06:48Z"}