Time Series Analysis and Multivariate Statistical Analysis

Abstract

Research was carried out mainly in the areas of time series analysis and multivariate statistical analysis. The most important results in the first area apply to autoregressive and moving average processes. In the second area emphasis was on parameter consistency and elliptically contoured distributions. To estimate the parameters of the moving average model 16 different iterative procedures have been devised. These involve alternative parametrizations, time and frequency domain representations, Newton-Raphson and scoring approaches, and use of likelihoods and concentrated likelihoods. Properties of the likelihood function, as well as the estimates, have been derived. Keywords: Kalman filtering, Army research.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1988
Accession Number
ADA202273

Entities

People

  • Theodore W. Anderson

Organizations

  • Stanford University

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Consistency
  • Data Science
  • Estimators
  • Frequency
  • Frequency Domain
  • Information Science
  • Kalman Filtering
  • Kalman Filters
  • Military Research
  • Multivariate Analysis
  • Scientists
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Time Series Analysis

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.