A Bivariate First Order Autoregressive Time Series Model in Exponential Variables (BEAR(1))

Dewald, Lee S.; Lewis, Peter; McKenzie, E.

doi:10.21236/ada177055

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“…For further details and other models, see Lewis and Shedler (1979), Jacobs (1978Jacobs ( , 1980 and Dewald and Lewis (1985b).…”

Section: Multivariate Modelsmentioning

confidence: 99%

SOME SIMPLE MODELS FOR CONTINUOUS VARIATE TIME SERIES¹

Lewis

1985

J American Water Resour Assoc

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: A survey is given of recently developed 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 non–Gaussian models.

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“…For further details and other models, see Lewis and Shedler (1979), Jacobs (1978Jacobs ( , 1980 and Dewald and Lewis (1985b).…”

Section: Multivariate Modelsmentioning

confidence: 99%