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Suppose that a random process Z(s; t), indexed in space and time, has a spatio-temporal stationary covariance C(h; u), where h 2 IR d (d 1) is a spatial lag and u 2 IR is a temporal lag. Separable spatio-temporal covariances have the property that they can be written as a product of a purely spatial covariance and a purely temporal covariance. Their ease of(More)
Polar orbiting satellites remotely sense the earth and its atmosphere, producing data sets that give daily global coverage. For any given day, the data are many and spatially irregular. Our goal in this article is to predict values that are spatially regular at diierent resolutions; such values are often used as input to general circulation models (GCMs)(More)
Nonparametric hypothesis testing for a spatial signal can involve a large numberofhypotheses. For instance, two satellite images of the same scene, taken before and after an event, could be used to test a hypothesis that the event h a s no environmental impact. This is equivalent to testing that the mean diierence of \after;before" is zero at each of the(More)
In this article, we propose a regression method for simultaneous supervised clustering and feature selection over a given undirected graph, where homogeneous groups or clusters are estimated as well as informative predictors, with each predictor corresponding to one node in the graph and a connecting path indicating a priori possible grouping among the(More)