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Modelling non-normal first-order autoregressive time series

✍ Scribed by C. H. Sim

Publisher
John Wiley and Sons
Year
1994
Tongue
English
Weight
684 KB
Volume
13
Category
Article
ISSN
0277-6693

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✦ Synopsis

We shall first review some non-normal stationary first-order autoregressive models. The models are constructed with a given marginal distribution (logistic, hyperbolic secant, exponential, Laplace, or gamma) and the requirement that the bivariate joint distribution of the generated process must be sufficiently simple so that the parameter estimation and forecasting problems of the models can be addressed. A model-building approach that consists of model identification, estimation, diagnostic checking, and forecasting is then discussed for this class of models. KEY WORDS Model building methodology Non-normal AR( 1) models Monte Carlo simulation Bootstrap technique CCC 0277-6693/94/040369-13

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