SK4FGA: Scott-Knott for Forensic Glass Analysis

In forensics, it is common and effective practice to analyse glass fragments from the scene and suspects to gain evidence of placing a suspect at the crime scene. This kind of analysis involves comparing the physical and chemical attributes of glass fragments that exist on both the person and at the crime scene, and assessing the significance in a likeness that they share. The package implements the Scott-Knott Modification 2 algorithm (SKM2) (Christopher M. Triggs and James M. Curran and John S. Buckleton and Kevan A.J. Walsh (1997) <doi:10.1016/S0379-0738(96)02037-3> "The grouping problem in forensic glass analysis: a divisive approach", Forensic Science International, 85(1), 1–14) for small sample glass fragment analysis using the refractive index (ri) of a set of glass samples. It also includes an experimental multivariate analog to the Scott-Knott algorithm for similar analysis on glass samples with multiple chemical concentration variables and multiple samples of the same item; testing against the Hotellings T^2 distribution (J.M. Curran and C.M. Triggs and J.R. Almirall and J.S. Buckleton and K.A.J. Walsh (1997) <doi:10.1016/S1355-0306(97)72197-X> "The interpretation of elemental composition measurements from forensic glass evidence", Science & Justice, 37(4), 241–244).

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: Rcpp
LinkingTo: Rcpp
Published: 2023-01-30
Author: Toby Hayward [aut, cre] (Main developer and maintainer of the package.), James Curran [aut, ctb] (Supervised and contributed to the development of the package.), Lewis Kendall-Jones [ctb] (Wrote and supported the development of the C++ code.)
Maintainer: Toby Hayward <tobyhayward13 at gmail.com>
BugReports: https://github.com/tobyhayward13/SCI118UOA_ForensicGlassAnalysis/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/tobyhayward13/SCI118UOA_ForensicGlassAnalysis
NeedsCompilation: yes
CRAN checks: SK4FGA results

Documentation:

Reference manual: SK4FGA.pdf

Downloads:

Package source: SK4FGA_0.1.1.tar.gz
Windows binaries: r-prerel: SK4FGA_0.1.1.zip, r-release: SK4FGA_0.1.1.zip, r-oldrel: SK4FGA_0.1.1.zip
macOS binaries: r-prerel (arm64): SK4FGA_0.1.1.tgz, r-release (arm64): SK4FGA_0.1.1.tgz, r-oldrel (arm64): SK4FGA_0.1.1.tgz, r-prerel (x86_64): SK4FGA_0.1.1.tgz, r-release (x86_64): SK4FGA_0.1.1.tgz
Old sources: SK4FGA archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SK4FGA to link to this page.