Development of Statistical Techniques to Better Utilize Data Characterized by Being Below Instrument Detection Thresholds and by Small Sample Size.

Abstract

Estimation of parametric families for small data sets where a significant portion of the data lay below fixed instrument detection thresholds was investigated. Thus the number of data points was random (an example of Type I censoring). Both analytic and simulation procedures were utilized. In particular, maximum likelihood techniques, order statistic techniques, truncation techniques, fill-in with constants, and fill-in with expected values of the missing points were investigated. For exponential data, truncation seemed most appropriate while for normal and log-normal data, fill-in with expected values (modified to correct for conditioning on the number of data points) was best. The criteria for selection was the total square error. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Oct 24, 1983
Accession Number
ADA135408

Entities

People

  • A. S. Gleit

Tags

Communities of Interest

  • Advanced Electronics
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computers
  • Data Science
  • Data Sets
  • Detection
  • Estimators
  • Information Science
  • Normal Distribution
  • Order Statistics
  • Random Variables
  • Reliability
  • Simulations
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics
  • Stochastic Processes

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Statistical inference.