Readiness Evaluations Using Multivariate Data Reduction

Abstract

Several statistical methods--principal component analysis, orthogonal factor analysis, classification, and clustering techniques--are tailored and combined into a system designed to digest high-dimensional vectors of data on operational readiness of Navy ships. Such data consist of large numbers of scores for individual ships assigned by experts. The purpose of the data reduction system is to provide a robust method of representing the data by a small number of scores that are meaningfully related to the original scores and that allow classification and clustering of the ships into homogeneous groups on relevant readiness scales. Simulated data drawn from mixtures of specified multivariate normal populations have been used to test the ability of the system to recover individual populations and to detect trends over time.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA063758

Entities

People

  • S. Zacks
  • W. H. Marlow
  • Zeev Barzily

Organizations

  • George Washington University

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computer Programs
  • Data Reduction
  • Data Science
  • Data Sets
  • Digital Information
  • Discriminant Analysis
  • Electronic Countermeasures
  • Factor Analysis
  • Information Processing
  • Information Science
  • Knowledge Management
  • Logistics
  • Military Research
  • Normal Distribution
  • Operational Readiness
  • Statistics
  • Two Dimensional

Readers

  • Maritime and Naval Warfare Studies
  • Neural Network Machine Learning.
  • Regression Analysis.