Stationary mixture transition distribution (MTD) models via predictive distributions |
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Authors: | Ramsés H Mena Stephen G Walker |
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Institution: | 1. Departamento de Probabilidad y Estadística, Universidad National Autonoma de México, A.P. 20-726, México, D.F. 01000, Mexico;2. University of Kent, UK |
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Abstract: | This paper combines two ideas to construct autoregressive processes of arbitrary order. The first idea is the construction of first order stationary processes described in Pitt et al. (2002). Constructing first order autoregressive models via latent processes. Scand. J. Statist.29, 657–663] and the second idea is the construction of higher order processes described in Raftery (1985). A model for high order Markov chains. J. Roy. Statist. Soc. B.47, 528–539]. The resulting models provide appealing alternatives to model non-linear and non-Gaussian time series. |
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Keywords: | 62M10 62A15 |
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