Time Series Analysis of RTC Great Lakes Recruit Graduate Data

Abstract

This thesis formulates predictions for Recruit Training Command (RTC) Great Lakes' recruit graduation rates based on two econometric approaches. The Navy's recruit graduation rates exhibit pronounced seasonal and long-term behaviors, which tends to cause logistical problems at RTC. The modeling and subsequent forecast of RTC graduation rates is therefore an important management tool which could facilitate future planning for both RTC Great Lakes and the U.S. Navy. First the multiplicative decomposition method is employed to produce a model. As an alternative the autoregressive integrated moving average (ARIMA) process is used to describe the data. In both instances, satisfactory forecasting results are attained.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1998
Accession Number
ADA359541

Entities

People

  • Edward F. Bosque

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Autocorrelation
  • Basic Training
  • Data Sets
  • Decomposition
  • Delphi Method
  • Great Lakes
  • Lakes
  • Mathematical Models
  • Models
  • Noise
  • Seasonal Variations
  • Standards
  • Time Series Analysis
  • Training
  • United States
  • Visual Inspection

Readers

  • Materials Science.
  • Statistical inference.
  • Theoretical Analysis.