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Sensor networks aim at monitoring events and phenomena occurring in their environment and providing useful information to one or several end users.When a global knowledge of sensed data is needed, techniques from data gathering, statistical estimation and parametric modeling can be used. While the two first methods require respectively a large amount of energy and a knowledge of statistical dependencies between measurements, a new simple algorithm for fitting a parametric model to sensed data is proposed in this article. The novelty and advantages of this approach stands in its intrinsic robustness to packet losses and asynchronous data exchanges. Moreover, this algorithm is intituively efficient as it uses the broadcasting nature of the wireless medium.