Aircraft Airframe Cost Estimation Utilizing a Components of Variance Model.

Abstract

Previous studies into airframe acquisition cost estimation do not explicitly recognize the existence of correlation in the historical data. If one believes this data problem exists, then it is possible to develop a components of variance model that takes the problem into account. It is a more general model that recognizes two sources of error: (1) error due to different types of airframes and (2) overall or ordinary regression error. The variance of these two errors can be estimated and then can be utilized along with the technique of generalized least squares to obtain a cost estimating relationship which explicitly accounts for the data correlation. This modeling technique, when compared to techniques presently in service, shows that present estimating relationships underestimate the variance of the cost prediction of a new type airframe and overestimate the variance of the cost prediction of a follow-on airframe. Also, those existing techniques which implicitly recognize data correlation do not make use of all the data information available and therefore produce estimates with poor confidence prediction intervals.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1976
Accession Number
ADA032627

Entities

People

  • Ronald C. Marcotte

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Acquisition
  • Aerospace Industry
  • Air Force
  • Air Force Facilities
  • Aircrafts
  • Airframes
  • Computer Programs
  • Data Science
  • Databases
  • Department Of Defense
  • Engineering
  • Estimators
  • Information Science
  • Intervals
  • Manufacturing
  • Military Aircraft
  • New York

Readers

  • Life Cycle Cost Analysis
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks