Rainfall Modelling Using a Latent Gaussian Variable
نویسندگان
چکیده
A monotonic transformation is applied to hourly rainfall data to achieve marginal normality. This deenes a latent Gaussian variable, with zero rainfall corresponding to censored values below a threshold. Autocor-relations of the latent v ariable are estimated by maximum likelihood. The goodness of t of the model to Edinburgh rainfall data is comparable with that of existing point process models. Gibbs sampling is used to disaggre-gate daily rainfall data, to generate typical hourly data conditional on daily totals.
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