Space-time modelling without distance

We present a novel method for analysing space-time data when response data is given at a nite number of locations and the aim is to predict the response at a new location, where only a short run of data is available. This is the type of dataset that is typically available when attempting to analyse wind velocity data and we demonstrate our method, and compare it to that introduced by Haslett and Raftery (1989), on a set of data collected from the island of Crete in Greece. Typically the distance between locations is used to deene the correlation matrix between responses at distinct locations even though this cannot always be justiied. The peculiarity presented in our data is that the sites are in a complex topography so diierences in the local characteristics of the wind stations, the direction of the prevailing winds, and other unobserved covariates can all lead to unsuitable model tting. We use a nonparametric model to avoid these problems and demonstrate its predictive power in relation to the dataset under study.