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An algorithm for maximum likehood estimation in regular exponential families is proposed. The algorithm is a modification of the well-known iterative proportional scaling algorithm used for estimating loglinear models for contingency tables. As illustration, the algorithm is applied to an example from the class of graphical association models (Lauritzen and Wermuth, 1989).