A Bootstrap Algorithm for Mixture Models and Interval Data in Inter-Comparisons

Abstract

To combine the information from several laboratories to output a representative value chi(sub r) and its probability distribution function is the main aim of an inter-comparison in Metrology. Here, the proposed procedure identifies a simple model for this probability function, by taking into account only the probability interval estimates as a measure of the uncertainty in each laboratory. A mixture density model is chosen to characterize the stochastic variability of the inter-comparison population considered as a whole. The bootstrap method is applied to approximate the distribution function of the comparison output in an automatic way.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2001
Accession Number
ADP013724

Entities

People

  • F. Pavese
  • G. Regoliosi
  • P. Ciarlini

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computations
  • Data Science
  • Distribution Functions
  • Estimators
  • Information Science
  • Intervals
  • Measurement
  • Models
  • Monte Carlo Method
  • Normal Distribution
  • Probabilistic Models
  • Probability
  • Probability Distribution Functions
  • Probability Distributions
  • Random Variables

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Forest Ecology
  • Regression Analysis.