Leandro Pardo

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We first give an expression for the amount of information supplied by a probabilistic experiment, whose elementary events are characterized by both their probabilities and some qualitative weights. This measure is called “order-a weighted information energy,” and it is a generalization of the weighted information energy given by Theodorescu and studied(More)
In this paper we consider inference based on very general divergence measures, under assumptions of multinomial sampling and loglinear models. We define the minimum φ-divergence estimator, which is seen to be a generalization of the maximum likelihood estimator. This estimator is then used in a φ-divergence goodness-of-fit statistic, which is the basis of(More)