Accession Number : ADA115754

Title :   Extension of Some Models for Positive-Valued Time Series.

Descriptive Note : Doctoral thesis,

Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s) : Hugus,David Kennedy

PDF Url : ADA115754

Report Date : Mar 1982

Pagination or Media Count : 358

Abstract : Time series models with autoregressive, moving average and mixed autoregressive-moving average correlation structure and with positive-valued non-normal marginal distribution are considered. First, a flexible mixed model GLARMA(p,q) with Gamma marginals is investigated. The correlation structure for several special cases is derived. For the first-order autoregressive case, GLAR(1), the conditional density of X sub n given X sub n-1 is derived. This leads to the formation of a likelihood function and a numerical approximation to and a simulation study of the maximum likelihood method of parameter estimation. Multivariate extensions of the model are considered briefly. Second, three methods for generating first-order moving average sequences with Exponential marginals are examined. These generalize the EMA (1) Exponential model. Negative correlation using antithetic variables is investigated in the moving average models. A preliminary analysis of wind speed data obtained over a 15-year period in the Gulf of Alaska is presented. A model with four harmonic deterministic mean multiplying random innovative factors modeled by a GLAR (1) process is developed. Correlograms and periodograms are used to determine the model for the mean and the structure of the innovation process. (Author)

Descriptors :   *Linear regression analysis, *Automatic, *Communication and radio systems, *Weighting functions, *Models, Correlation techniques, Determinants(Mathematics), Estimates, Harmonics, Time series analysis, Approximation(Mathematics), Simulation, Wind velocity, Numerical analysis, Simulators, Mean, Value, Probability, Theses

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE