Assessing evidentiary value in fire debris analysis by chemometric and likelihood ratio approaches  Michael E. Sigman, Mary R. Williams  Forensic Science International  Volume 264, Pages 113-121 (July 2016) DOI: 10.1016/j.forsciint.2016.03.051 Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 1 Receiver operating characteristic (ROC) space showing points from previous discrete classification results for in silico and research burn fire debris data. The square, triangle and diamond symbols represent LDA, QDA and SIMCA model results, respectively. Open symbols represent in silico cross-validation results, and filled symbols represent fire debris result. The solid circle symbol represents proficiency test results from 2011 (see text for additional information). Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 2 Receiver operating characteristic curves for SVM=solid line, LDA=dashed, QDA=dotted and kNN=dash-dot, models applied to in silico validation data. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 3 Detection error trade-off plots for (a) SVM (b) LDA (c) QDA and (d) kNN models applied to the in silico validation data. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 4 Tippett plots for (a) SVM (b) LDA (c) QDA and (d) kNN models applied to the in silico validation data. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 5 Empirical cross entropy (ECE) plots for (a) SVM (b) LDA (c) QDA and (d) kNN models. Dotted curve shows the neutral reference method where the L is always equal to one, the solid curve is validation LR values calculated at different prior odds, the dashed curve is the validation LR values after optimal calibration by the pool adjacent violator (PAV) algorithm. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 6 Receiver operating characteristic curves for SVM=solid line, LDA=dashed, QDA=dotted and kNN=dash-dot, models applied to fire debris validation data. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 7 Detection error trade-off plots for (a) SVM (b) LDA (c) QDA and (d) kNN models applied to the fire debris validation data. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Fig. 8 Empirical cross entropy (ECE) plots for (a) SVM (b) LDA (c) QDA and (d) kNN models applied to the fire debris validation data. Dotted curve shows the neutral reference method where the LR is always equal to one, the solid curve is validation LR values calculated at different prior odds, the dashed curve is the validation LR values after optimal calibration by the pool adjacent violator (PAV) algorithm. Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions

Forensic Science International 2016 264, 113-121DOI: (10. 1016/j Forensic Science International 2016 264, 113-121DOI: (10.1016/j.forsciint.2016.03.051) Copyright © 2016 Elsevier Ireland Ltd Terms and Conditions