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                            Library & Multimedia
 U-statistics for estimating performance metrics in forensic handwriting analysis
NCJ Number
              301875
Journal

*Journal of Statistical Computation and Simulation* Volume: 90 Issue: 6 Dated: 2020 Pages: 1082-1117
Author(s)
          C. Fuglsby;
                        et al
Date Published

2020
Length
              36 pages
Annotation
              Noting that a class of computationally efficient approximations to a set of natural U-statistics and related U-processes that arise in forensic and biometric comparisons have been developed, this article details the asymptotic characterization of the natural U-statistics, the development of computationally efficient approximations, and expected error bounds of said approximations.
Abstract
              The developed statistical methods are presented in the context of forensic handwriting comparisons and are used to estimate the rate at which the random match probability (RMP) decreases as a function of the amount of writing available in the comparison samples. Although presented in a forensic handwriting comparison context, similar problems arise in machine learning or pattern recognition where the task is to classify a batch of exchangeable objects that arise from the same class. Similarly, the developed methods can be used to estimate the rate at which the error rate decreases as the number of objects to be classified increases. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2009-DN-BX-K234
                                2014-IJ-CX-K088


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Award
        Quantifying the Effects of Database Size and Sample Quality on Measures of Individualization Validity and Accuracy in Forensics
                                Foundational Research into the Quantification of the Value of Forensic Evidence for Complex Evidential Forms arising from Impression and Pattern Evidence
    
  
  
Date Published: January 1, 2020
    
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