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).
- Version0.1.1
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release01/30/2023
Team
Toby Hayward
James Curran
Show author detailsRolesAuthor, ContributorLewis Kendall-Jones
Show author detailsRolesContributor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Linking To1 package