Some Simple Models for Continuous Variate Time Series.

Abstract

A survey is given of recently developed mathematical models for continuous variate non-Gaussian time series. The emphasis is on marginally specific models with given correlation structure. Exponential, Gamma, Weibull, Laplace, Beta, and Mixed Exponential models are considered for the marginal distributions of the stationary time series. Most of the models are random coefficient, additive linear models. Some discussion of the meaning of autoregression and linearity is given, as well as suggestions for higher-order linear residual analysis for nonGaussian models. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1985
Accession Number
ADA158451

Entities

People

  • Peter A.W. Lewis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • California
  • Computational Science
  • Computer Science
  • Data Science
  • Difference Equations
  • Equations
  • Gaussian Processes
  • Information Science
  • Mathematical Models
  • Military Research
  • Models
  • Probability
  • Random Variables
  • Stationary Processes
  • Statistical Analysis
  • Stochastic Processes
  • Surveys

Fields of Study

  • Mathematics

Readers

  • Statistical inference.