Applications: Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbourne's Rainfall

By Rob J Hyndman, Gary K. Grunwald. 2000

49 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Soil Science

View Paper: https://www.semanticscholar.org/paper/699ff4b6b305b5e783eaf7361ba4f55d93ebd284

Citations in the corpus

• Theory & Methods: Non‐Gaussian Conditional Linear AR(1) Models (2000, unknown): “(More sophisticated models could impose a binary Markov chain to allow for periods with no rain, along with a positive AR(1) model for rain amounts — see e.g. Stern & Coe, 1984; c© Australian Statistical Publishing Association Inc. 2000 Grunwald & Jones, 1999; Hyndman & Grunwald, 2000.)”
• Weather Forecasting for Weather Derivatives (2005, unknown): “The analyses of Harvey (1989), Hyndman and Grunwald (2000), Milionis and Davies (1994), Visser and Molenaar (1995), Jones (1996), and Pozo, Esteban-Parra, Rodrigo, and Castro-Diez (1998) suggest its value, for example, but they do not address the intrayear temperature forecasting relevant to our…”