On Periodic and Multiple Autoregressions

Abstract

A methodology is presented for analyzing periodic autoregressions which is also applicable when inferring the second order properties of periodically correlated processes. In addition, capitalizing on the duality between periodic and multiple autoregressions, a method is set forth for analyzing the latter, which overcomes the usual requirements of a large number of both parameters and computer storage locations.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1976
Accession Number
ADA030759

Entities

People

  • Marcello Pagano

Organizations

  • University at Buffalo

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Covariance
  • Data Science
  • Equations
  • Estimators
  • Gaussian Processes
  • Information Science
  • Military Research
  • Multivariate Analysis
  • New York
  • Random Variables
  • Stationary
  • Stationary Processes
  • Statistical Algorithms
  • Statistical Estimation
  • Statistics
  • Time Series Analysis

Readers

  • International Relations, focusing on Korea-Africa and North Korea-South Korea relations, and Nigeria-Latin American Relations.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms