Moving Average Models--Time Series in M-Dimensions.

Abstract

Stochastic models for discrete time series in the time domain are well known but such models lack consideration of spatial dependency. We expand on their work by constructing spatially depending moving average models. Definitions of order, stationarity, invertibility, autocorrelation function, and spectrum are made as natural extensions of those in zero dimensions and are implemented in the one and two-space dimensional models. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 15, 1978
Accession Number
ADA054585

Entities

People

  • C. A. Oprian
  • D. A. Voss
  • L. A. Aroian

Organizations

  • Union College

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Autocorrelation
  • Correlation Techniques
  • Data Science
  • Equations
  • Human Geography
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • New York
  • Power Spectra
  • Spectra
  • Stationary Processes
  • Statistical Analysis
  • Statistics
  • Universities
  • White Noise

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Statistical inference.

Technology Areas

  • Space