Improved Forecasting Methods for Naval Manpower Studies

Abstract

Forecasted manpower inventory, the number of individuals available in a given time period, are derived from stay/loss models, where estimates of the probability of staying in the navy informs the advancement and gains modules used within the Department of the Navy. As such, the accuracy of these probability rates is critical to these related functions. Extending an earlier study, we focus on two methodologies, autoregressive and logistic methods, and consider the effect of structural changes on forecast accuracy. Exogenous events or structural breaks in time-series data can result in large forecasting errors. Using the Bai-Perron (BP) test, we determine if structural breaks occur in the data. In cases where breaks are identified we control for breaks in the models. We then validate and discuss improvements in the forecast accuracy.

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Document Details

Document Type
Technical Report
Publication Date
Mar 25, 2015
Accession Number
ADA614084

Entities

People

  • Ping Y. Bellamy
  • Tanja F. Blackstone

Organizations

  • Navy Personnel Research, Studies, and Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Contracts
  • Data Mining
  • Delphi Method
  • Errors
  • Information Science
  • Instructors
  • Inventory
  • Management Personnel
  • Manpower
  • Military Research
  • Naval Personnel
  • Probability
  • Standards
  • Statistics
  • Students
  • War Colleges

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Naval Personnel Management