Durbán, MaríaGlasbey, C.A.2006-11-082006-11-082001-03http://hdl.handle.net/10016/157We propose a vector autoregressive moving average process as a model for daily weather data. For the rainfall variable a monotonic transformation is applied to achieve marginal normality, thus defining a latent variable, with zero rainfall data corresponding to censored values below a threshold. Methodology is presented for model identification, estimation and validation, illustrated using data from Mynefield, Scotland. The new model, a VARMA(2,1) process, fits the data and produces more realistic simulated series than existing methods dur to Richardson (1981) and Peiris and McNicol (1996).339621 bytesapplication/pdfengworking paperEstadísticaopen accessws011610