Prediction of Changeover Performance: Operational Test (OT) Parameters from Developmental Test (DT) Parameters via Meta-Analysis

Abstract

This paper sketches and examines some analytical statistical concepts and methodologies that should usefully inform and sharpen the process of military test and evaluation decision making. The concepts fall into the broad category of combining information. Developmental testing (DT) refers to the testing of a new or upgraded system in the course of its technical engineering development. Operational testing (OT) is conducted later by operational military personnel in the field. Because of the rigors of field operation there is the expectation that OT failure rates are related to, but likely to be higher, than DT failure rates. The relationship between DT and OT failure rates is modeled and estimation of model parameters examined. A likelihood-based pooling of observations from sensors with a range-dependent precision is studied. Alternatives to the circular normal dispersion model are examined and estimation of the model parameters sketched; experience shows that in projectile testing it is often the case that some individual shots deviate from aimpoint more wildly than described by the customary circular normal model.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1997
Accession Number
ADA328590

Entities

People

  • Arthur Fries
  • Donald P. Gaver Jr.
  • Patricia A. Jacobs

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Business Administration
  • Data Analysis
  • Data Sets
  • Developmental Tests
  • Dispersions
  • Engineering
  • Military Personnel
  • Miss Distance
  • Observation
  • Operations Research
  • Precision
  • Random Variables
  • Shape
  • Statistics
  • Test And Evaluation
  • Test Methods

Readers

  • Computational Modeling and Simulation
  • Naval Mine Countermeasure Systems Development.
  • Statistical inference.