Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: Forensic Fire Debris Analysis

    Authors

    M. R. Williams; M. E. Sigman; J. Lewis;K. M. Pitan

    Comments

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    Abbreviated Journal Title

    Forensic Sci.Int.

    Keywords

    Fire debris; Factor analysis; Bayesian decision theory; Pattern; classification; Chemometrics; GAS CHROMATOGRAPHY/MASS SPECTROMETRY; AUTOMOTIVE GASOLINE SAMPLES; MASS-SPECTROMETRY; IGNITABLE LIQUIDS; COVARIANCE; MATRIX; Medicine, Legal

    Abstract

    A Bayesian soft classification method combined with target factor analysis (TFA) is described and tested for the analysis of fire debris data. The method relies on analysis of the average mass spectrum across the chromatographic profile (i.e., the total ion spectrum, TIS) from multiple samples taken from a single fire scene. A library of TIS from reference ignitable liquids with assigned ASTM classification is used as the target factors in TFA. The class-conditional distributions of correlations between the target and predicted factors for each ASTM class are represented by kernel functions and analyzed by Bayesian decision theory. The soft classification approach assists in assessing the probability that ignitable liquid residue from a specific ASTM E1618 class, is present in a set of samples from a single fire scene, even in the presence of unspecified background contributions from pyrolysis products. The method is demonstrated with sample data sets and then tested on laboratory-scale burn data and large-scale field test burns. The overall performance achieved in laboratory and field test of the method is approximately 80% correct classification of fire debris samples. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

    Journal Title

    Forensic Science International

    Volume

    222

    Issue/Number

    1-3

    Publication Date

    1-1-2012

    Document Type

    Article

    Language

    English

    First Page

    373

    Last Page

    386

    WOS Identifier

    WOS:000308690600059

    ISSN

    0379-0738

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