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SOME SIMPLE MODELS FOR CONTINUOUS VARIATE TIME SERIES 1
Author(s) -
Lewis P. A. W.
Publication year - 1985
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1985.tb05378.x
Subject(s) - random variate , weibull distribution , mathematics , series (stratigraphy) , laplace transform , exponential function , gaussian , autoregressive model , statistical physics , natural exponential family , residual , marginal distribution , gamma distribution , statistics , simple (philosophy) , random variable , exponential family , mathematical analysis , algorithm , physics , paleontology , quantum mechanics , biology , philosophy , epistemology
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.