Dynamic Linear Models with Leading Indicators. Revision.

Abstract

This thesis proposes a dynamic linear model (DLM) to deal with the problem of forecasting with leading indicators. We call this type of a DLM as a dynamic linear model with leading indicators. Our approach expands the conventional one-dimension DLMs to the two dimension case. Analyses of some real data sets which initially motivated us to explore our approach, are used as applications. For reasons of confidentiality they have been coded as Data Set One, Data Set Two and Data Set Three, respectively. Our approach has a much wider field of application, for instances, the two-dimension filter problems in image processing, and estimation problems related to Markov random fields.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA293929

Entities

People

  • Jingxian Chen

Organizations

  • George Washington University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Bayesian Networks
  • Data Analysis
  • Data Sets
  • Delphi Method
  • Equations
  • Filters
  • Filtration
  • Gaussian Distributions
  • Image Processing
  • Indicators
  • Information Science
  • Military Research
  • Models
  • Monte Carlo Method
  • Normal Distribution
  • Observation
  • Two Dimensional

Readers

  • Computational Modeling and Simulation
  • Computer Science.