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Markov models for time series with mixed distribution

โœ Scribed by Gary K. Grunwald; Richard H. Jones

Publisher
John Wiley and Sons
Year
2000
Tongue
English
Weight
161 KB
Volume
11
Category
Article
ISSN
1180-4009

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โœฆ Synopsis

We consider modelling time series of amounts which may be zero using a stochastic ยฎrst-order Markov model with mixed transition density having a discrete component at 0 and a continuous component describing non-zero amounts. The models extend chain-dependent stochastic models in the literature on modelling rainfall. Under certain assumptions the Markov chain likelihood can be factored to allow model parameters to be estimated by maximum likelihood using standard Generalized Linear Models methods and software. The results give estimates of seasonal patterns in mean amounts and probability distributions of amounts. We illustrate with 30 years of daily rainfall data from Melbourne, Australia.

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