Time Series in M Dimensions: Spatial Models.

Abstract

The general theory of stationary spatial models is developed: namely MA, moving average; AR, autoregressive; and ARMA, autoregressive moving average processes. As compared to the time series in m dimensions, spatial models may be one-sided, two-sided, or mixed. Free use is made of the previous results of Aroian and his associates in time series in m dimensions. The main theoretical properties of the models in the univariate case are established. The multivariate case is even more important than the univariate. Estimation by minimum variance and simulation of the models are included. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 25, 1980
Accession Number
ADA091734

Entities

People

  • Leo A. Aroian
  • Omer Gebizlioglu

Organizations

  • Union College

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Computations
  • Confidence Limits
  • Coordinate Systems
  • Covariance
  • Data Science
  • Economic Analysis
  • Equations
  • Information Science
  • Knowledge Management
  • Military Research
  • Power Spectra
  • Simulations
  • Stationary
  • Stationary Processes
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Statistical inference.